A novel multitracking system for the evaluation of high-level swimmers performances

摘要

Swimmer tracking has specific difficulties compared to the other tracking systems due to some complex problems such as occlusion (by another person, a wall or splashing), variability of the target (in appearance, lighting or behavior). For the sake of conceiving a robust swimmer tracking system we started by developing mono-tracking systems based on some well-known pattern recognition techniques such as optical correlation (Non-linear JTC (Joint Transform Correlator)) and histogram based approaches (Color histogram, LBP (Local Binary Patterns) and HOG (Histogram of Oriented Gradients)). As an enhancement to these systems, we introduce the aspect of multi-tracking. Its basic idea is to track several potential targets which will give us several tracks then we choose the best track and relaunch the multi-tracking process. Forasmuch each technique has its own periods of good tracking and dropouts (loss of the object to be tracked), we propose a novel heterogeneous multi-tracking system by taking advantage of different tracking techniques. Each track represents an independent mono-tracking system. The use of the proposed heterogeneous multi-tracking system has improved significantly the tracking results from 81.34% to 94%.