Compressed domain moving object detection by spatio-temporal analysis of H.264/AVC syntax elements

Laumer M, Amon P, Hutter A, Kaup A (2015)


Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2015

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 282-286

Article Number: 7170091

Event location: Cairns AU

ISBN: 9781479977833

DOI: 10.1109/PCS.2015.7170091

Abstract

In this paper, we present a novel moving object detection algorithm for H.264/AVC-compressed video streams. The algorithm does not require full decoding up to the pixel domain but only parsing the compressed bit streams. Thereby, only syntax elements for reconstructing (sub-)macroblock types and quantization parameters are extracted. These features are used to segment the video frames into foreground and background and, according to this segmentation, to identify regions containing moving objects. In a first step, (sub-)macroblock types are analyzed to create initial maps indicating for each block the 'weight' for the presence of a moving object. These maps serve as input for our novel spatio-temporal detection algorithm to refine the weight indicating the level of motion for each block. Finally, quantization parameters of macroblocks are used to apply individual thresholds to the block weights to segment the video frames. Experimental results show that our approach efficiently identifies regions containing moving objects and that the presented algorithm is suitable for processing a large number of video streams in parallel.

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How to cite

APA:

Laumer, M., Amon, P., Hutter, A., & Kaup, A. (2015). Compressed domain moving object detection by spatio-temporal analysis of H.264/AVC syntax elements. In Proceedings of the 31st Picture Coding Symposium, PCS 2015 - with 2015 Packet Video Workshop, PV 2015 (pp. 282-286). Cairns, AU: Institute of Electrical and Electronics Engineers Inc..

MLA:

Laumer, Marcus, et al. "Compressed domain moving object detection by spatio-temporal analysis of H.264/AVC syntax elements." Proceedings of the 31st Picture Coding Symposium, PCS 2015 - with 2015 Packet Video Workshop, PV 2015, Cairns Institute of Electrical and Electronics Engineers Inc., 2015. 282-286.

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