This paper presents a real-time single-camera surveillance system, aiming at detecting and partly analyzing a group of people. A set of moving persons is segmented using a combination of the Gaussian Mixture Model (GMM) and the Dynamic Markov Random Fields (DMRF) technique. For a better extraction of the human silhouettes, the energy function of DMRF is extended with texture information. The mean-shift algorithm is utilized to track multiple people over the sequence. To address the human-occlusion problem, we model the horizontal projection histograms of the human silhouettes using a nonlinear regression algorithm. This model enables to automatically locate the people during the occlusions. Experiments show that the proposal has nearly same performance (also with occlusion) as the particle-filter with the benefit of being a factor of 10-20 faster in computing.
|Title of host publication||IEEE International Conference on Multimedia and Expo, 2008 : Hannover, Germany, 23 - 26 June 2008|
|Place of Publication||Piscataway|
|Publisher||Institute of Electrical and Electronics Engineers|
|Publication status||Published - 2008|