Advances in Multimedia The latest articles from Hindawi Publishing Corporation © 2015 , Hindawi Publishing Corporation . All rights reserved. High-Level Codewords Based on Granger Causality for Video Event Detection Tue, 23 Jun 2015 06:20:45 +0000 Video event detection is a challenging problem in many applications, such as video surveillance and video content analysis. In this paper, we propose a new framework to perceive high-level codewords by analyzing temporal relationship between different channels of video features. The low-level vocabulary words are firstly generated after different audio and visual feature extraction. A weighted undirected graph is constructed by exploring the Granger Causality between low-level words. Then, a greedy agglomerative graph-partitioning method is used to discover low-level word groups which have similar temporal pattern. The high-level codebooks representation is obtained by quantification of low-level words groups. Finally, multiple kernel learning, combined with our high-level codewords, is used to detect the video event. Extensive experimental results show that the proposed method achieves preferable results in video event detection. Shao-nian Huang, Dong-jun Huang, and Mansoor Ahmed Khuhro Copyright © 2015 Shao-nian Huang et al. All rights reserved. A New Information Hiding Method Based on Improved BPCS Steganography Thu, 26 Mar 2015 07:31:30 +0000 Bit-plane complexity segmentation (BPCS) steganography is advantageous in its capacity and imperceptibility. The important step of BPCS steganography is how to locate noisy regions in a cover image exactly. The regular method, black-and-white border complexity, is a simple and easy way, but it is not always useful, especially for periodical patterns. Run-length irregularity and border noisiness are introduced in this paper to work out this problem. Canonical Cray coding (CGC) is also used to replace pure binary coding (PBC), because CGC makes use of characteristic of human vision system. Conjugation operation is applied to convert simple blocks into complex ones. In order to contradict BPCS steganalysis, improved BPCS steganography algorithm adopted different bit-planes with different complexity. The higher the bit-plane is, the smaller the complexity is. It is proven that the improved BPCS steganography is superior to BPCS steganography by experiment. Shuliang Sun Copyright © 2015 Shuliang Sun. All rights reserved. Video Superresolution Reconstruction Using Iterative Back Projection with Critical-Point Filters Based Image Matching Thu, 12 Mar 2015 06:22:33 +0000 To improve the spatial resolution of reconstructed images/videos, this paper proposes a Superresolution (SR) reconstruction algorithm based on iterative back projection. In the proposed algorithm, image matching using critical-point filters (CPF) is employed to improve the accuracy of image registration. First, a sliding window is used to segment the video sequence. CPF based image matching is then performed between frames in the window to obtain pixel-level motion fields. Finally, high-resolution (HR) frames are reconstructed based on the motion fields using iterative back projection (IBP) algorithm. The CPF based registration algorithm can adapt to various types of motions in real video scenes. Experimental results demonstrate that, compared to optical flow based image matching with IBP algorithm, subjective quality improvement and an average PSNR score of 0.53 dB improvement are obtained by the proposed algorithm, when applied to video sequence. Yixiong Zhang, Mingliang Tao, Kewei Yang, and Zhenmiao Deng Copyright © 2015 Yixiong Zhang et al. All rights reserved. An Improved Saliency Detection Approach for Flying Apsaras in the Dunhuang Grotto Murals, China Tue, 24 Feb 2015 06:40:29 +0000 Saliency can be described as the ability of an item to be detected from its background in any particular scene, and it aims to estimate the probable location of the salient objects. Due to the salient map that computed by local contrast features can extract and highlight the edge parts including painting lines of Flying Apsaras, in this paper, we proposed an improved approach based on a frequency-tuned method for visual saliency detection of Flying Apsaras in the Dunhuang Grotto Murals, China. This improved saliency detection approach comprises three important steps: (1) image color and gray channel decomposition; (2) gray feature value computation and color channel convolution; (3) visual saliency definition based on normalization of previous visual saliency and spatial attention function. Unlike existing approaches that rely on many complex image features, this proposed approach only used local contrast and spatial attention information to simulate human’s visual attention stimuli. This improved approach resulted in a much more efficient salient map in the aspect of computing performance. Furthermore, experimental results on the dataset of Flying Apsaras in the Dunhuang Grotto Murals showed that the proposed visual saliency detection approach is very effective when compared with five other state-of-the-art approaches. Zhong Chen, Shengwu Xiong, Qingzhou Mao, Zhixiang Fang, and Xiaohan Yu Copyright © 2015 Zhong Chen et al. All rights reserved. Improving Shape Retrieval by Integrating AIR and Modified Mutual NN Graph Wed, 28 Jan 2015 11:54:45 +0000 In computer vision, image retrieval remained a significant problem and recent resurgent of image retrieval also relies on other postprocessing methods to improve the accuracy instead of solely relying on good feature representation. Our method addressed the shape retrieval of binary images. This paper proposes a new integration scheme to best utilize feature representation along with contextual information. For feature representation we used articulation invariant representation; dynamic programming is then utilized for better shape matching followed by manifold learning based postprocessing modified mutual NN graph to further improve the similarity score. We conducted extensive experiments on widely used MPEG-7 database of shape images by so-called bulls-eye score with and without normalization of modified mutual NN graph which clearly indicates the importance of normalization. Finally, our method demonstrated better results compared to other methods. We also computed the computational time with another graph transduction method which clearly shows that our method is computationally very fast. Furthermore, to show consistency of postprocessing method, we also performed experiments on challenging ORL and YALE face datasets and improved baseline results. Nouman Qadeer, Dongting Hu, Xiabi Liu, Shahzad Anwar, and Malik Saad Sultan Copyright © 2015 Nouman Qadeer et al. All rights reserved. A Rate-Distortion Optimized Coding Method for Region of Interest in Scalable Video Coding Mon, 12 Jan 2015 06:45:49 +0000 The support for region of interest (ROI) browsing, which allows dropping background part of video bitstreams, is a desirable feature for video applications. With the help of the slice group technique provided by H.264/SVC, rectangular ROI areas can be encoded into separate ROI slices. Additionally, by imposing certain constraints on motion estimation, ROI part of the bitstream can be decoded without background slices of the same layer. However, due to the additional spatial and temporal constraints applied to the encoder, overall coding efficiency would be significantly decreased. In this paper, a rate-distortion optimized (RDO) encoding scheme is proposed to improve the coding efficiency of ROI slices. When background slices are discarded, the proposed method uses base layer information to generate the prediction signal of the enhancement layer. Thus, the temporal constraints can be loosened during the encoding process. To do it in this way, the possible mismatch between generated reference frames and original ones is also considered during rate-distortion optimization so that a reasonable trade-off between coding efficiency and decoding drift can be made. Besides, a new Lagrange multiplier derivation method is developed for further coding performance improvement. Experimental results demonstrate that the proposed method achieves significant bitrate saving compared to existing methods. Hongtao Wang, Dong Zhang, and Houqiang Li Copyright © 2015 Hongtao Wang et al. All rights reserved. A Simple and Robust Gray Image Encryption Scheme Using Chaotic Logistic Map and Artificial Neural Network Wed, 31 Dec 2014 00:10:35 +0000 A robust gray image encryption scheme using chaotic logistic map and artificial neural network (ANN) is introduced. In the proposed method, an external secret key is used to derive the initial conditions for the logistic chaotic maps which are employed to generate weights and biases matrices of the multilayer perceptron (MLP). During the learning process with the backpropagation algorithm, ANN determines the weight matrix of the connections. The plain image is divided into four subimages which are used for the first diffusion stage. The subimages obtained previously are divided into the square subimage blocks. In the next stage, different initial conditions are employed to generate a key stream which will be used for permutation and diffusion of the subimage blocks. Some security analyses such as entropy analysis, statistical analysis, and key sensitivity analysis are given to demonstrate the key space of the proposed algorithm which is large enough to make brute force attacks infeasible. Computing validation using experimental data with several gray images has been carried out with detailed numerical analysis, in order to validate the high security of the proposed encryption scheme. Adelaïde Nicole Kengnou Telem, Colince Meli Segning, Godpromesse Kenne, and Hilaire Bertrand Fotsin Copyright © 2014 Adelaïde Nicole Kengnou Telem et al. All rights reserved. A Natural Image Pointillism with Controlled Ellipse Dots Wed, 24 Dec 2014 00:10:04 +0000 This paper presents an image-based artistic rendering algorithm for the automatic Pointillism style. At first, ellipse dot locations are randomly generated based on a source image; then dot orientations are precalculated with help of a direction map; a saliency map of the source image decides long and short radius of the ellipse dot. At last, the rendering runs layer-by-layer from large size dots to small size dots so as to reserve the detailed parts of the image. Although only ellipse dot shape is adopted, the final Pointillism style performs well because of variable characteristics of the dot. Dongxiang Chi Copyright © 2014 Dongxiang Chi. All rights reserved. Automatic Image Tagging Model Based on Multigrid Image Segmentation and Object Recognition Mon, 22 Dec 2014 09:21:03 +0000 Since rapid growth of Internet technologies and mobile devices, multimedia data such as images and videos are explosively growing on the Internet. Managing large scale multimedia data with correct tags and annotations is very important task. Incorrect tags and annotations make it hard to manage multimedia data. Accurate tags and annotation ease management of multimedia data and give high quality retrieve results. Fully manual image tagging which is tagged by user will be most accurate tags when the user tags correct information. Nevertheless, most of users do not make effort on task of tagging. Therefore, we suffer from lots of noisy tags. Best solution for accurate image tagging is to tag image automatically. Robust automatic image tagging models are proposed by many researchers and it is still most interesting research field these days. Since there are still lots of limitations in automatic image tagging models, we propose efficient automatic image tagging model using multigrid based image segmentation and feature extraction method. Our model can improve the object descriptions of images and image regions. Our method is tested with Corel dataset and the result showed that our model performance is efficient and effective compared to other models. Woogyoung Jun, Yillbyung Lee, and Byoung-Min Jun Copyright © 2014 Woogyoung Jun et al. All rights reserved. Deblurring by Solving a TVp-Regularized Optimization Problem Using Split Bregman Method Tue, 16 Dec 2014 09:19:50 +0000 Image deblurring is formulated as an unconstrained minimization problem, and its penalty function is the sum of the error term and TVp-regularizers with . Although TVp-regularizer is a powerful tool that can significantly promote the sparseness of image gradients, it is neither convex nor smooth, thus making the presented optimization problem more difficult to deal with. To solve this minimization problem efficiently, such problem is first reformulated as an equivalent constrained minimization problem by introducing new variables and new constraints. Thereafter, the split Bregman method, as a solver, splits the new constrained minimization problem into subproblems. For each subproblem, the corresponding efficient method is applied to ensure the existence of closed-form solutions. In simulated experiments, the proposed algorithm and some state-of-the-art algorithms are applied to restore three types of blurred-noisy images. The restored results show that the proposed algorithm is valid for image deblurring and is found to outperform other algorithms in experiments. Su Xiao Copyright © 2014 Su Xiao. All rights reserved. No-Reference Video Quality Assessment Model for Distortion Caused by Packet Loss in the Real-Time Mobile Video Services Thu, 11 Dec 2014 06:35:54 +0000 Packet loss will make severe errors due to the corruption of related video data. For most video streams, because the predictive coding structures are employed, the transmission errors in one frame will not only cause decoding failure of itself at the receiver side, but also propagate to its subsequent frames along the motion prediction path, which will bring a significant degradation of end-to-end video quality. To quantify the effects of packet loss on video quality, a no-reference objective quality assessment model is presented in this paper. Considering the fact that the degradation of video quality significantly relies on the video content, the temporal complexity is estimated to reflect the varying characteristic of video content, using the macroblocks with different motion activities in each frame. Then, the quality of the frame affected by the reference frame loss, by error propagation, or by both of them is evaluated, respectively. Utilizing a two-level temporal pooling scheme, the video quality is finally obtained. Extensive experimental results show that the video quality estimated by the proposed method matches well with the subjective quality. Jiarun Song and Fuzheng Yang Copyright © 2014 Jiarun Song and Fuzheng Yang. All rights reserved. Reliability Model Construction for Complex System Based on Common Cause Failure Network Wed, 10 Dec 2014 11:21:10 +0000 A new construction method of system reliability was proposed in this paper based on network and relevant failure. Taking the component units as the nodes and the interaction relationships between the nodes as the side lines, a new directional network reliability model with certain network topology characteristics was constructed. It can indicate the complex topology relationship, interaction mechanism, and the transmission mechanism of failure affect between mechanical integration and electrical integration of system components. Compared with the traditional research methods, the relevant failure was considered during this process. Through the application of the fault data in the bogie system of high-speed train, it was shown that a new network reliability model which considered the relevant failure can be constructed by the method proposed in this paper and the result can be more accurate, especially for the complex mechanical and electrical integration systems. Lijie Li, Limin Jia, and Yanhui Wang Copyright © 2014 Lijie Li et al. All rights reserved. Augmented Reality Experience: From High-Resolution Acquisition to Real Time Augmented Contents Wed, 10 Dec 2014 08:02:04 +0000 This paper presents results of a research project “dUcale” that experiments ICT solutions for the museum of Palazzo Ducale (Urbino). In this project, the famed painting the “Città Ideale” becomes a case to exemplify a specific approach to the digital mediation of cultural heritage. An augmented reality (AR) mobile application, able to enhance the museum visit experience, is presented. The computing technologies involved in the project (websites, desktop and social applications, mobile software, and AR) constitute a persuasive environment for the artwork knowledge. The overall goal of our research is to provide to cultural institutions best practices efficiently on low budgets. Therefore, we present a low cost method for high-resolution acquisition of paintings; the image is used as a base in AR approach. The proposed methodology consists of an improved SIFT extractor for real time image. The other novelty of this work is the multipoint probabilistic layer. Experimental results demonstrated the robustness of the proposed approach with extensive use of the AR application in front of the “Città Ideale” painting. To prove the usability of the application and to ensure a good user experience, we also carried out several users tests in the real scenario. Paolo Clini, Emanuele Frontoni, Ramona Quattrini, and Roberto Pierdicca Copyright © 2014 Paolo Clini et al. All rights reserved. Top-Down and Bottom-Up Cues Based Moving Object Detection for Varied Background Video Sequences Sun, 16 Nov 2014 11:48:45 +0000 Moving object detection is a crucial and critical task for any surveillance system. Conventionally, a moving object detection task is performed on the basis of consecutive frame difference or background models which are based on some mathematical aspects or probabilistic approaches. But, these approaches are based on some initial conditions and short amount of time is needed to learn all these models. Also, the bottleneck in all these previous approaches is that they require neat and clean background or need to create a background first by using some approaches and that it is essential to update them regularly to cope with the illuminating changes. In this paper, moving object detection is executed using visual attention where there is no need for background formulation and updates as it is background independent. Many bottom-up approaches and one combination of bottom-up and top-down approaches are proposed in the present paper. The proposed approaches seem more efficient due to inessential requirement of learning background model and due to being independent of previous video frames. Results indicate that the proposed approach works even against slight movements in the background and in various outdoor conditions. Chirag I. Patel, Sanjay Garg, Tanish Zaveri, and Asim Banerjee Copyright © 2014 Chirag I. Patel et al. All rights reserved. Chaos Based Joint Compression and Encryption Framework for End-to-End Communication Systems Sun, 09 Nov 2014 07:19:22 +0000 Augmentation in communication and coding technology has made encryption an integral part of secure multimedia communication systems. Security solution for end-to-end image transmission requires content adaptation at intermediate nodes, which consumes significant resources to decrypt, process, and reencrypt the secured data. To save the computational resources, this paper proposes a network-friendly encryption technique, which can be implemented in transparency to content adaptation techniques. The proposed encryption technique maintains the compression efficiency of underlying entropy coder, and enables the processing of encrypted data. Thorough analysis of the technique, as regards various standard evaluation parameters and attack scenarios, demonstrates its ability to withstand known-plaintext, ciphertext-only, and approximation attacks. This justifies its implementation for secure image transmission for end-to-end communication systems. Nidhi Goel, Balasubramanian Raman, and Indra Gupta Copyright © 2014 Nidhi Goel et al. All rights reserved. A Novel Approach for Optimal Multimedia Data Distribution in Mobile Cloud Computing Thu, 23 Oct 2014 11:21:33 +0000 With the integration of mobile computing and cloud computing, more diverse services can be provided to the users, supporting the mobility feature of mobile computing along with the power of cloud computing. This new paradigm still faces challenges, especially in terms of performance. When it comes to multimedia data communication, thin clients (such as smart phones and tablets) suffer because of performance and power constraints. Previously done studies have trivially addressed this problem. Therefore, in our paper, we present a framework in which thick clients (laptop or desktop computers) are incorporated into mobile cloud paradigm with attention paid to user mobility. Its objective is to optimize the distribution of multimedia content between the cloud and the thin clients. Our work comes up with both numerical analysis and simulation to justify the validity and the effectiveness of the proposal approach. Pham Phuoc Hung, Mohammad Aazam, Tien-Dung Nguyen, and Eui-Nam Huh Copyright © 2014 Pham Phuoc Hung et al. All rights reserved. Execution Behavior Modeling Methodology for Large Scale Surveillance System Design and Evaluation Tue, 14 Oct 2014 00:00:00 +0000 This paper presents a performance and evaluation environment for complex surveillance system design. The system consists of environment model, execution model, and application and evaluation model. The environment model interprets the script and creates objects in a surveillance environment so that various situations can be evaluated. The execution model modifies generated data with the perspective of each sensor and reflects algorithm execution behavior. The application model allows building large scale collaborative operations. The system behavior is parameterized for simple representations. The feasibility of the proposed method is illustrated through the case studies for improving the prototype surveillance system. Jung-Min Oh, Kyung Hoon Kim, Sangjin Hong, and Nammee Moon Copyright © 2014 Jung-Min Oh et al. All rights reserved. Text Extraction from Historical Document Images by the Combination of Several Thresholding Techniques Mon, 29 Sep 2014 00:00:00 +0000 This paper presents a new technique for the binarization of historical document images characterized by deteriorations and damages making their automatic processing difficult at several levels. The proposed method is based on hybrid thresholding combining the advantages of global and local methods and on the mixture of several binarization techniques. Two stages have been included. In the first stage, global thresholding is applied on the entire image and two different thresholds are determined from which the most of image pixels are classified into foreground or background. In the second stage, the remaining pixels are assigned to foreground or background classes based on local analysis. In this stage, several local thresholding methods are combined and the final binary value of each remaining pixel is chosen as the most probable one. The proposed technique has been tested on a large collection of standard and synthetic documents and compared with well-known methods using standard measures and was shown to be more powerful. Toufik Sari, Abderrahmane Kefali, and Halima Bahi Copyright © 2014 Toufik Sari et al. All rights reserved. Object Tracking with Adaptive Multicue Incremental Visual Tracker Tue, 23 Sep 2014 00:00:00 +0000 Generally, subspace learning based methods such as the Incremental Visual Tracker (IVT) have been shown to be quite effective for visual tracking problem. However, it may fail to follow the target when it undergoes drastic pose or illumination changes. In this work, we present a novel tracker to enhance the IVT algorithm by employing a multicue based adaptive appearance model. First, we carry out the integration of cues both in feature space and in geometric space. Second, the integration directly depends on the dynamically-changing reliabilities of visual cues. These two aspects of our method allow the tracker to easily adapt itself to the changes in the context and accordingly improve the tracking accuracy by resolving the ambiguities. Experimental results demonstrate that subspace-based tracking is strongly improved by exploiting the multiple cues through the proposed algorithm. Jiang-tao Wang, De-bao Chen, Jing-ai Zhang, Su-wen Li, and Xing-jun Wang Copyright © 2014 Jiang-tao Wang et al. All rights reserved. Adaptive Media Streaming to Mobile Devices: Challenges, Enhancements, and Recommendations Wed, 10 Sep 2014 09:52:36 +0000 Video streaming is predicted to become the dominating traffic in mobile broadband networks. At the same time, adaptive HTTP streaming is developing into the preferred way of streaming media over the Internet. In this paper, we evaluate how different components of a streaming system can be optimized when serving content to mobile devices in particular. We first analyze the media traffic from a Norwegian network and media provider. Based on our findings, we outline benefits and challenges for HTTP streaming, on the sender and the receiver side, and we investigate how HTTP-based streaming affects server performance. Furthermore, we discuss various aspects of efficient coding of the video segments from both performance and user perception point of view. The final part of the paper studies efficient adaptation and delivery to mobile devices over wireless networks. We experimentally evaluate and improve adaptation strategies, multilink solutions, and bandwidth prediction techniques. Based on the results from our evaluations, we make recommendations for how an adaptive streaming system should handle mobile devices. Small changes, or simple awareness of how users perceive quality, can often have large effects. Kristian Evensen, Tomas Kupka, Haakon Riiser, Pengpeng Ni, Ragnhild Eg, Carsten Griwodz, and Pål Halvorsen Copyright © 2014 Kristian Evensen et al. All rights reserved. An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations Mon, 04 Aug 2014 07:24:06 +0000 To avoid the staircase artifacts, an adaptive image denoising model is proposed by the weighted combination of Tikhonov regularization and total variation regularization. In our model, Tikhonov regularization and total variation regularization can be adaptively selected based on the gradient information of the image. When the pixels belong to the smooth regions, Tikhonov regularization is adopted, which can eliminate the staircase artifacts. When the pixels locate at the edges, total variation regularization is selected, which can preserve the edges. We employ the split Bregman method to solve our model. Experimental results demonstrate that our model can obtain better performance than those of other models. Kui Liu, Jieqing Tan, and Benyue Su Copyright © 2014 Kui Liu et al. All rights reserved. Novel Intermode Prediction Algorithm for High Efficiency Video Coding Encoder Mon, 30 Jun 2014 08:18:57 +0000 The joint collaborative team on video coding (JCT-VC) is developing the next-generation video coding standard which is called high efficiency video coding (HEVC). In the HEVC, there are three units in block structure: coding unit (CU), prediction unit (PU), and transform unit (TU). The CU is the basic unit of region splitting like macroblock (MB). Each CU performs recursive splitting into four blocks with equal size, starting from the tree block. In this paper, we propose a fast CU depth decision algorithm for HEVC technology to reduce its computational complexity. In  PU, the proposed method compares the rate-distortion (RD) cost and determines the depth using the compared information. Moreover, in order to speed up the encoding time, the efficient merge SKIP detection method is developed additionally based on the contextual mode information of neighboring CUs. Experimental result shows that the proposed algorithm achieves the average time-saving factor of 44.84% in the random access (RA) at Main profile configuration with the HEVC test model (HM) 10.0 reference software. Compared to HM 10.0 encoder, a small BD-bitrate loss of 0.17% is also observed without significant loss of image quality. Chan-seob Park, Gwang-Soo Hong, and Byung-Gyu Kim Copyright © 2014 Chan-seob Park et al. All rights reserved. A New One-Dimensional Chaotic Map and Its Use in a Novel Real-Time Image Encryption Scheme Mon, 02 Jun 2014 07:29:03 +0000 We present a new one-dimensional chaotic map, suitable for real-time image encryption. Its theoretical analysis, performed using some specific tools from the chaos theory, shows that the proposed map has a chaotic regime and proves its ergodicity, for a large space of values of the control parameter. In addition, to argue for the good cryptographic properties of the proposed map, we have tested the randomness of the values generated by its orbit using NIST statistical suite. Moreover, we present a new image encryption scheme with a classic bimodular architecture, in which the confusion and the diffusion are assured by means of two maps of the previously proposed type. The very good cryptographic performances of the proposed scheme are proved by an extensive analysis, which was performed regarding the latest methodology in this field. Radu Boriga, Ana Cristina Dăscălescu, and Adrian-Viorel Diaconu Copyright © 2014 Radu Boriga et al. All rights reserved. An Improved Fast Mode Decision Method for H.264/AVC Intracoding Tue, 20 May 2014 08:54:43 +0000 An improved fast and efficient mode decision method for H.264/AVC intracoding is proposed, which is based on the analysis of the gravity center method and more efficient mode selection. In contrast to the fast mode decision method where the intramodes are determined by the gravity center of the block, the mass center vector is computed for the block and the subblocks formed by the proposed subsampling techniques. This method is able to determine all correlation directions of the block that correspond to the intraprediction mode directions of the H.264/AVC. On this basis, only a small number of intraprediction modes are chosen as the best modes for rate-distortion optimization (RDO) calculation. Different video sequences are used to test the performance of the proposed method. Experimental results reveal the significant computational savings achieved with slight peak signal-to-noise ratio (PSNR) degradation and bit-rate increase. Abderrahmane Elyousfi Copyright © 2014 Abderrahmane Elyousfi. All rights reserved. A IEEE 802.11e HCCA Scheduler with a Reclaiming Mechanism for Multimedia Applications Thu, 20 Mar 2014 17:45:01 +0000 The QoS offered by the IEEE 802.11e reference scheduler is satisfactory in the case of Constant Bit Rate traffic streams, but not yet in the case of Variable Bit Rate traffic streams, whose variations stress its scheduling behavior. Despite the numerous proposed alternative schedulers with QoS, multimedia applications are looking for refined methods suitable to ensure service differentiation and dynamic update of protocol parameters. In this paper a scheduling algorithm, Unused Time Shifting Scheduler (UTSS), is deeply analyzed. It is designed to cooperate with a HCCA centralized real-time scheduler through the integration of a bandwidth reclaiming scheme, suitable to recover nonexhausted transmission time and assign that to the next polled stations. UTSS dynamically computes with an complexity transmission time providing an instantaneous resource overprovisioning. The theoretical analysis and the simulation results highlight that this injection of resources does not affect the admission control nor the centralized scheduler but is suitable to improve the performance of the centralized scheduler in terms of mean access delay, transmission queues length, bursts of traffic management, and packets drop rate. These positive effects are more relevant for highly variable bit rate traffic. Anna Lina Ruscelli and Gabriele Cecchetti Copyright © 2014 Anna Lina Ruscelli and Gabriele Cecchetti. All rights reserved. Salt and Pepper Noise Removal with Noise Detection and a Patch-Based Sparse Representation Thu, 13 Mar 2014 12:33:03 +0000 Images may be corrupted by salt and pepper impulse noise due to noisy sensors or channel transmission errors. A denoising method by detecting noise candidates and enforcing image sparsity with a patch-based sparse representation is proposed. First, noise candidates are detected and an initial guide image is obtained via an adaptive median filtering; second, a patch-based sparse representation is learnt from this guide image; third, a weighted - regularization method is proposed to penalize the noise candidates heavier than the rest of pixels. An alternating direction minimization algorithm is derived to solve the regularization model. Experiments are conducted for 30%∼90% impulse noise levels, and the simulation results demonstrate that the proposed method outperforms total variation and Wavelet in terms of preserving edges and structural similarity to the noise-free images. Di Guo, Xiaobo Qu, Xiaofeng Du, Keshou Wu, and Xuhui Chen Copyright © 2014 Di Guo et al. All rights reserved. Macroblock Layer Rate Control Based on Structural Similarity and Mean Absolute Difference for H.264 Tue, 11 Feb 2014 00:00:00 +0000 In the process of the H.264 video coding, special attention should be paid to the subjective quality of the image. This paper applies the structural similarity (SSIM) based subjective evaluation to the rate control in the H.264 coding and proposes to combine the SSIM and the mean absolute difference (MAD) to perform the macroblock layer bit allocation instead of the MAD. Experimental results show that the proposed method is correlating better with the human visual system and thus achieves better subjective image quality. Xiao Chen and Dongjue Gu Copyright © 2014 Xiao Chen and Dongjue Gu. All rights reserved. Heritage Multimedia and Children Edutainment: Assessment and Recommendations Sun, 09 Feb 2014 10:36:30 +0000 Despite the rising commodification of heritage sites and practices, children engagement in their own cultures remains incredibly low, greatly endangering the future preservation of nations’ unique nonrenewable resource. Considering children’s very early engagement with cultural attitudes and identities, it is increasingly critical to develop a deeply rooted culture of responsibility and conservation from the earliest years, ensuring that children naturally feel invested in their surroundings. Unfortunately, heritage education remains largely undervalued, with most efforts relying on in-person experiences in formal cultural institutions. This paper thus aims to explore how heritage education can be redefined, using some of the most innovative virtual imaging and artificial reality technologies to at once expand access and engagement with one’s own history. Though there have been introductory applications of this edutainment multimedia technology, it will require a multidisciplinary team to create heritage programming which is as entertaining as it is intellectually challenging for young children. With the rich resources of 3D imaging and interactive programming already at our disposal, we are well-equipped to do so, given a coordinated effort. Naif A. Haddad Copyright © 2014 Naif A. Haddad. All rights reserved. Real-Time QoS-Aware Video Streaming: A Comparative and Experimental Study Thu, 16 Jan 2014 12:49:15 +0000 Due to its flexibility, scalability, real-time, and rich QoS features, Data Distribution Service (DDS) middleware provides seamless integration with high-performance, real-time, and mission-critical networks. Unlike traditional client-server communication models, DDS is based on the publish/subscribe communication model. DDS improves video streaming quality through its efficient and high-performance data delivery mechanism. This paper studies and investigates how DDS is suitable for streaming real-time full-motion video over a communication network. Experimental studies are conducted to compare video streaming using a the VLC player with the DDS overlay. Our results depict the superiority of DDS in provisioning quality video streams at the cost of low network bandwidth. The results also show that DDS is more scalable and flexible and is a promised technology for video distribution over IP networks where it uses much less bandwidth while maintaining high quality video stream delivery. Basem Al-Madani, Anas Al-Roubaiey, and Zubair A. Baig Copyright © 2014 Basem Al-Madani et al. All rights reserved. Video Pulses: User-Based Modeling of Interesting Video Segments Sun, 12 Jan 2014 16:07:47 +0000 We present a user-based method that detects regions of interest within a video in order to provide video skims and video summaries. Previous research in video retrieval has focused on content-based techniques, such as pattern recognition algorithms that attempt to understand the low-level features of a video. We are proposing a pulse modeling method, which makes sense of a web video by analyzing users' Replay interactions with the video player. In particular, we have modeled the user information seeking behavior as a time series and the semantic regions as a discrete pulse of fixed width. Then, we have calculated the correlation coefficient between the dynamically detected pulses at the local maximums of the user activity signal and the pulse of reference. We have found that users' Replay activity significantly matches the important segments in information-rich and visually complex videos, such as lecture, how-to, and documentary. The proposed signal processing of user activity is complementary to previous work in content-based video retrieval and provides an additional user-based dimension for modeling the semantics of a social video on the web. Markos Avlonitis and Konstantinos Chorianopoulos Copyright © 2014 Markos Avlonitis and Konstantinos Chorianopoulos. All rights reserved.