Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Background Modeling and Subtraction of Dynamic Scenes
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Illumination Normalization with Time-Dependent Intrinsic Images for Video Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion-based background subtraction using adaptive kernel density estimation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Robust color histogram descriptors for video segment retrieval and identification
IEEE Transactions on Image Processing
A new key frame representation for video segment retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Video analysis via nonlinear dimensionality reduction
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
| Hi-index | 0.00 |
In this work we present an overview of several methods that extract information from a video segment using pixel-wise histograms or pixel-wise probability distributions. We will show that most of these algorithms that have been presented in the literature are specific implementations of a more general approach. Finally, we will present some applications based on these ideas to video segment retrieval and target detection in surveillance applications with static and dynamic backgrounds. We present a visual segment descriptor based on pixel-wise histograms that outperforms similar reviewed methods. In this way we show the advantages on this approach for this kind of problems.