In this paper, we solve the problem of human detection in crowded scenes using a Bayesian 3D model based method. Human candidates are first nominated by a ...
The main contribution of the proposed method is a candidate optimization procedure which balances between the greedy optimization method and global optimization.
Jun 14, 2015 · In this paper, we solve the problem of human detection in crowded scenes using a Bayesian 3D model based method. Human candidates are first ...
... model shape hier-archy is automatically constructed for efficient model matching. ... using Markov random field for simultaneous humandetection and segmentation.
Missing: 3D | Show results with:3D
This work poses the problem of segmenting individual humans in crowded situations from stationary video camera sequences as a "model-based segmentation" ...
Bayesian 3D model based human detection in crowded scenes using efficient optimization · Lu WangN. Yung. Computer Science. 2011 IEEE Workshop on Applications of ...
In this paper, we solve the problem of human detection in crowded scenes using a Bayesian 3D model based method. Human candidates are first nominated by a ...
Lu Wang, Nelson Yung, "Bayesian 3D model based human detection in crowded scenes using efficient optimization", Proceedings of the IEEE. Workshop on ...
In this paper we develop a fully 3D Bayesian approach for tracking an unknown and changing number of people in a scene using video taken from a single, fixed ...
This tracker utilises a Dynamic Bayesian Network for predicting objects' positions through filtering and updating in real-time.