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The Scientific World Journal
Volume 2014, Article ID 832871, 9 pages
http://dx.doi.org/10.1155/2014/832871
Research Article

Nonuniform Video Size Reduction for Moving Objects

1Department of Electrical and Electronic Engineering, Dongguk University-Seoul, Seoul 100-715, Republic of Korea
2Department of Multimedia Engineering, Dongguk University-Seoul, Seoul 100-715, Republic of Korea

Received 19 June 2014; Revised 4 August 2014; Accepted 15 August 2014; Published 31 August 2014

Academic Editor: Young-Sik Jeong

Copyright © 2014 Anh Vu Le et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Moving objects of interest (MOOIs) in surveillance videos are detected and encapsulated by bounding boxes. Since moving objects are defined by temporal activities through the consecutive video frames, it is necessary to examine a group of frames (GoF) to detect the moving objects. To do that, the traces of moving objects in the GoF are quantified by forming a spatiotemporal gradient map (STGM) through the GoF. Each pixel value in the STGM corresponds to the maximum temporal gradient of the spatial gradients at the same pixel location for all frames in the GoF. Therefore, the STGM highlights boundaries of the MOOI in the GoF and the optimal bounding box encapsulating the MOOI can be determined as the local areas with the peak average STGM energy. Once an MOOI and its bounding box are identified, the inside and outside of it can be treated differently for object-aware size reduction. Our optimal encapsulation method for the MOOI in the surveillance videos makes it possible to recognize the moving objects even after the low bitrate video compressions.