Patches in Vision
Call for Papers
The smallest primitive employed for describing an image is the pixel. However, analyzing an image as an ensemble of patches (i.e., spatially adjacent pixels/descriptors which are treated collectively as a single primitive), rather than individual pixels/descriptors, has some inherent advantages (i.e., computation, generalization, context, etc.) for numerous image and video content extraction applications (e.g., matching, correspondence, tracking, rendering, etc.). Common descriptors in literature, other than pixels, have been contours, shape, flow, and so forth.
Recently, many inroads have been made into novel tasks in image and video content extraction through the employment of patch-based representations with machine learning and pattern recognition techniques. Some of these novel areas include (but are not limited to):
- Object recognition/detection/tracking
- Event recognition/detection
- Structure from motion/multiview
In this special issue, we are soliciting papers from the image/video processing, computer vision, and pattern recognition communities that expand and explore the boundaries of patch representations in image and video content extraction.
Relevant topics to the issue include (but are not limited to):
- Novel methods for identifying (e.g., SIFT, DoGs, Harris detector) and employing salient patches
- Techniques that explore criteria for deciding the size and shape of a patch based on image content and the application
- Approaches that explore the employment of multiple and/or heterogeneous patch sizes and shapes during the analysis of an image
- Applications that explore how important relative patch position is, and whether there are advantages in allowing those patches to move freely or in a constrained fashion
- Novel methods that explore and extend the concept of patches to video (e.g. space-time patches/volumes)
- Approaches that draw upon previous work in structural pattern recognition in order to improve current patch-based algorithms
- Novel applications that extend the concept of patch-based analysis to other, hitherto, nonconventional areas of image and video processing, computer vision, and pattern recognition
- Novel techniques for estimating dependencies between patches in the same image (e.g., 3D rotations) to improve matching/correspondence algorithmic performance
Authors should follow the EURASIP Journal on Image and Video Processing manuscript format described at the journal site http://www.hindawi.com/journals/ivp/. Prospective authors should submit an electronic copy of their complete manuscripts through the journal Manuscript Tracking System at http://mts.hindawi.com/, according to the following timetable:
| Manuscript Due | May 1, 2008 |
| First Round of Reviews | August 1, 2008 |
| Publication Date | November 1, 2008 |
Guest Editors
- Simon Lucey, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Tsuhan Chen, ECE Department, Carnegie Mellon University, Pittsburgh, PA, USA
