Proceedings Article10.1109/VSMM.2010.5665970
Activity recognition through multi-scale dynamic Bayesian network
Feng Chen,Wei Wang +1 more
- 13 Dec 2010
- pp 34-41
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TL;DR: This paper presents a hierarchical durational-state dynamic Bayesian network (HDS-DBN) to model two stochastic processes which are related to two appropriate scales in intelligent surveillance.
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Abstract: Activity recognition is one of the most challenging problems in the video-based surveillance and computer-vision. In this paper we propose a novel approach to recognize human activity in which we decompose an activity into multiple stochastic processes, each corresponding to one scale of motion details. We present a hierarchical durational-state dynamic Bayesian network(HDS-DBN) to model two stochastic processes which are related to two appropriate scales in intelligent surveillance. In this approach the features we extracted are divided into two classes: global features and local features, which are at two different spatial scales. The HDS-DBN model structure combines global features with local ones harmoniously. The effectiveness of our approach is demonstrated by the experiments.
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Citations
Human behavior analysis in video surveillance: A Social Signal Processing perspective
TL;DR: This paper is the first review analyzing this new trend in automated surveillance of human activities, proposing a structured snapshot of the state of the art and envisaging novel challenges in the surveillance domain where the cross-pollination of Computer Science technologies and Sociology theories may offer valid investigation strategies.
228
Modeling multi-object interactions using string of feature graphs
TL;DR: A novel generalized framework of activity representation and recognition based on a 'string of feature graphs (SFG)' model, which is motivated by success of time sequence analysis approaches in speech recognition, but modified in order to capture the spatio-temporal properties of individual actions, the interactions between objects, and speed of activity execution.
11
An Intelligent Video Surveillance Framework for Remote Monitoring
M. Sivarathinabala,S. Abirami +1 more
- 01 Jan 2013
TL;DR: An intelligent video surveillance system to enable remote monitoring of real time scenarios is developed and introduces intelligent analysis of single person activity to enhance the security system in home and also enriches the current video surveillance systems through an automatic identification of abnormal behavior of the person.
8
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