Multi-Camera Occlusion and Sudden-Appearance-Change Detection Using Hidden Markovian Chains

TL;DR

This paper introduces a multi-camera object tracking system that detects occlusions and sudden appearance changes using a hidden Markovian model, demonstrating reliable detection in surveillance scenarios.

Contribution

It presents a novel multi-camera tracking algorithm that effectively detects occlusions and appearance changes with a hidden Markovian approach, improving surveillance robustness.

Findings

Reliable detection of occlusions and appearance changes

Effective multi-camera tracking in surveillance

Validation through experimental results

Abstract

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.