8 citations · 15 across the 5 of their papers we have counts for
6 papers
Automatic Tracker Selection w.r.t Object Detection Performance
Duc Phu Chau, François Bremond, Monique Thonnat +1
The tracking algorithm performance depends on video content. This paper presents a new multi-object tracking approach which is able to cope with video content variations. First the…
Online Tracking Parameter Adaptation based on Evaluation
Duc Phu Chau, Julien Badie, François Bremond +1
Parameter tuning is a common issue for many tracking algorithms. In order to solve this problem, this paper proposes an online parameter tuning to adapt a tracking algorithm to var…
Object Tracking in Videos: Approaches and Issues
Duc Phu Chau, François Bremond, Monique Thonnat
Mobile object tracking has an important role in the computer vision applications. In this paper, we use a tracked target-based taxonomy to present the object tracking algorithms. T…
A multi-feature tracking algorithm enabling adaptation to context variations
Duc Phu Chau, François Bremond, Monique Thonnat
We propose in this paper a tracking algorithm which is able to adapt itself to different scene contexts. A feature pool is used to compute the matching score between two detected o…
Robust Mobile Object Tracking Based on Multiple Feature Similarity and Trajectory Filtering
Duc Phu Chau, François Bremond, Monique Thonnat +1
This paper presents a new algorithm to track mobile objects in different scene conditions. The main idea of the proposed tracker includes estimation, multi-features similarity meas…
Repairing People Trajectories Based on Point Clustering
Duc Phu Chau, Francois Bremond, Etienne Corvee +1
This paper presents a method for improving any object tracking algorithm based on machine learning. During the training phase, important trajectory features are extracted which are…