Multi-Camera Occlusion and Sudden-Appearance-Change Detection Using Hidden Markovian Chains
This addresses monitoring challenges in surveillance systems, but it appears incremental as it builds on existing tracking methods with a specific statistical model.
The paper tackles the problem of object tracking in multi-camera surveillance by detecting sudden-appearance changes and occlusions using a hidden Markovian statistical model, with experimental results confirming reliable detection.
This paper was originally submitted to Xinova as a response to a Request for Invention (RFI) on new event monitoring methods. In this paper, a new object tracking algorithm using multiple cameras for surveillance applications is proposed. The proposed system can detect sudden-appearance-changes and occlusions using a hidden Markovian statistical model. The experimental results confirm that our system detect the sudden-appearance changes and occlusions reliably.