Fast compressed domain motion detection in H.264 video streams for video surveillance applications
Publication: Research - peer-review › Article in proceedings – Annual report year: 2009
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Fast compressed domain motion detection in H.264 video streams for video surveillance applications. / Szczerba, Krzysztof; Forchhammer, Søren; Støttrup-Andersen, Jesper; Eybye, Peder Tanderup.
In: Proceedings, AVSS. IEEE, 2009. p. 478-483.Publication: Research - peer-review › Article in proceedings – Annual report year: 2009
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TY - GEN
T1 - Fast compressed domain motion detection in H.264 video streams for video surveillance applications
A1 - Szczerba,Krzysztof
A1 - Forchhammer,Søren
A1 - Støttrup-Andersen,Jesper
A1 - Eybye,Peder Tanderup
AU - Szczerba,Krzysztof
AU - Forchhammer,Søren
AU - Støttrup-Andersen,Jesper
AU - Eybye,Peder Tanderup
PB - IEEE
PY - 2009
Y1 - 2009
N2 - This paper presents a novel approach to fast motion detection in H.264/MPEG-4 advanced video coding (AVC) compressed video streams for IP video surveillance systems. The goal is to develop algorithms which may be useful in a real-life industrial perspective by facilitating the processing of large numbers of video streams on a single server. The focus of the work is on using the information in coded video streams to reduce the computational complexity and memory requirements, which translates into reduced hardware requirements and costs. The devised algorithm detects and segments activity based on motion vectors embedded in the video stream without requiring a full decoding and reconstruction of video frames. To improve the robustness to noise, a confidence measure based on temporal and spatial clues is introduced to increase the probability of correct detection. The algorithm was tested on indoor surveillance H.264 sequences.
AB - This paper presents a novel approach to fast motion detection in H.264/MPEG-4 advanced video coding (AVC) compressed video streams for IP video surveillance systems. The goal is to develop algorithms which may be useful in a real-life industrial perspective by facilitating the processing of large numbers of video streams on a single server. The focus of the work is on using the information in coded video streams to reduce the computational complexity and memory requirements, which translates into reduced hardware requirements and costs. The devised algorithm detects and segments activity based on motion vectors embedded in the video stream without requiring a full decoding and reconstruction of video frames. To improve the robustness to noise, a confidence measure based on temporal and spatial clues is introduced to increase the probability of correct detection. The algorithm was tested on indoor surveillance H.264 sequences.
U2 - 10.1109/AVSS.2009.78
DO - 10.1109/AVSS.2009.78
SN - 978-0-7695-3718-4
BT - Proceedings, AVSS
T2 - Proceedings, AVSS
SP - 478
EP - 483
ER -