Tools and Techniques for Video Performance Evaluation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Representing shape with a spatial pyramid kernel
Proceedings of the 6th ACM international conference on Image and video retrieval
Semantic Representation and Recognition of Continued and Recursive Human Activities
International Journal of Computer Vision
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
A survey on vision-based human action recognition
Image and Vision Computing
Properties of optimally weighted data fusion in CBMIR
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Towards high-level human activity recognition through computer vision and temporal logic
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
Human activity analysis: A review
ACM Computing Surveys (CSUR)
Human detection using oriented histograms of flow and appearance
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Action recognition by dense trajectories
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Particle filters for state estimation of jump Markov linear systems
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
This paper presents work on integrating multiple computer vision-based approaches to surveillance video analysis to support user retrieval of video segments showing human activities. Applied computer vision using real-world surveillance video data is an extremely challenging research problem, independently of any information retrieval (IR) issues. Here we describe the issues faced in developing both generic and specific analysis tools and how they were integrated for use in the new TRECVid interactive surveillance event detection task. We present an interaction paradigm and discuss the outcomes from face-to-face end user trials and the resulting feedback on the system from both professionals, who manage surveillance video, and computer vision or machine learning experts. We propose an information retrieval approach to finding events in surveillance video rather than solely relying on traditional annotation using specifically trained classifiers.