Probabilistic Modeling of Dynamic Traffic Flow across Non-Overlapping Camera Views

In this paper, we propose a probabilistic method to model the dynamic traffic flow across nonoverlapping camera views. By assuming the transition time of object movement follows a certain global model, we may infer the time-varying traffic status in the unseen region without performing explicit object correspondence between camera views. In this paper, we model object correspondence and parameter estimation as a unified problem under the proposed EM (Expectation-Maximization) based framework. By treating object correspondence as a latent random variable, the proposed framework can iteratively search for the optimal model parameters with the implicit consideration of object correspondence.

• Type: Conference
• Year: 2010
• Where: ICPR
• Authors: Ching-Chun Huang, Wei-Chen Chiu, Sheng-Jyh Wang, Jen-Hui Chuang
• Keywords: Camera Views, Computer Vision, Explicit Object Correspondence, ICPR 2010, Object Correspondence