Rapid Object Tracking on Compressed Video
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
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Machine Vision and Applications - Special issue: IEEE WACV
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ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
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Multimedia Tools and Applications
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Proceedings of the 6th ACM international conference on Image and video retrieval
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EURASIP Journal on Applied Signal Processing
Lightweight object tracking in compressed video streams demonstrated in region-of-interest coding
EURASIP Journal on Applied Signal Processing
Multiple moving object detection for fast video content description in compressed domain
EURASIP Journal on Advances in Signal Processing
Moving object tracking in H.264/AVC bitstream
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
Shot boundary detection for H.264/AVC bitstreams with frames containing multiple types of slices
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
Object tracking using background subtraction and motion estimation in MPEG videos
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
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IEEE Transactions on Circuits and Systems for Video Technology
Object tracking for retrieval applications in MPEG-2
IEEE Transactions on Circuits and Systems for Video Technology
Video object segmentation: a compressed domain approach
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Efficient region-of-interest scalable video coding with adaptive bit-rate control
Advances in Multimedia
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We present methods to efficiently analyze scalable, compressed H.264/scalable video coding (SVC) video streams. Relying solely on information present in the compressed stream, we estimate the global camera motion, perform motion segmentation and use a simple matching process to track moving objects over time. Object energy images are constructed in order to help resolve the problem of object correspondence during the occlusions of multiple objects. To save computing time, we analyze lower spatial layers of the stream and add higher layer information only if necessary. We draw 2-D object trajectories in the view plane of the camera and use the temporal evolution of the objects' properties to estimate the relative distance to the camera, resulting in a pseudo 3-D representation of the trajectories. Finally, the suitability of the motion parameters to perform video retrieval/copy detection tasks is demonstrated. We therefore form two simple descriptors that are invariant to a series of transformations.