vic: a flexible framework for packet video
Proceedings of the third ACM international conference on Multimedia
Tracking and Object Classification for Automated Surveillance
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Optimal Dynamic Rate Shaping for Compressed Video Streaming
ICN '01 Proceedings of the First International Conference on Networking-Part 2
Real Time Face and Object Tracking as a Component of a Perceptual User Interface
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Constrained and general dynamic rate shaping of compressed digital video
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
A Distributed Visual Surveillance System
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Invariant Feature Extraction and Biased Statistical Inference for Video Surveillance
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Prioritized Region of Interest Coding in JPEG2000
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
KNIGHT/spl trade/: a real time surveillance system for multiple and non-overlapping cameras
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Content-adaptive utility-based video adaptation
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Support for effective use of multiple video streams in security
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Rate-accuracy tradeoff in automated, distributed video surveillance systems
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Effects of presenting geographic context on tracking activity between cameras
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
DOTS: support for effective video surveillance
Proceedings of the 15th international conference on Multimedia
Compress-image quality measures in image-processing applications
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Survey on contemporary remote surveillance systems for public safety
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Video quality for face detection, recognition, and tracking
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Reducing frame rate for object tracking
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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Large-scale distributed video surveillance systems pose new scalability challenges. Due to the large number of video sources in such systems, the amount of bandwidth required to transmit video streams for monitoring often strains the capability of the network. On the other hand, large-scale surveillance systems often rely on computer vision algorithms to automate surveillance tasks. We observe that these surveillance tasks present an opportunity for trade-off between the accuracy of the tasks and the bit rate of the video being sent. This paper shows that there exists a sweet spot, which we term critical video quality that can be used to reduce video bit rate without significantly affecting the accuracy of the surveillance tasks. We demonstrate this point by running extensive experiments on standard face detection and face tracking algorithms. Our experiments show that face detection works equally well even if the quality of compression is significantly reduced, and face tracking still works even if the frame rate is reduced to 6 frames per second. We further develop a prototype video surveillance system to demonstrate this idea. Our evaluation shows that we can achieve up to 29 times reduction in video bit rate when detecting faces and 16 times reduction when tracking faces. This paper also proposes a formal rate-accuracy optimization framework which can be used to determine appropriate encoding parameters in distributed video surveillance systems that are subjected to either bandwidth constraints or accuracy constraints.