Active Tracking Using Kernel-Based Vision Processor and Robust Fuzzy Control
- Alireza Mustafa 0, Moteaal Asadi Shirzi, Muhammad Reza Hairi Yazdi
- Corresponding Author
- Alireza Mustafa
0Control and Robotics Lab., University of Tehran
Available Online October 2006.
- https://doi.org/10.2991/jcis.2006.276How to use a DOI?
- Tracking, Fuzzy Control, Mean Shift Algorithm, Kernel Based Tracking, Parallel Processing
- In this paper we introduce a practicable system by combining a vision processing algorithm and a fuzzy controller to obtain an efficient active tracker. Target tracking performance is heavily dependent on a good blend of vision algorithm and control. Because of performance and computational complexity, in practice, many visual tracking algorithms cannot be linked with control systems to track objects in real-time. Robustness and speed are the two major bottlenecks of current visual tracking algorithms. In this paper, the target's visual model is used along with a kernel-based searching algorithm to predict the target position. A model update is also incorporated to recognize when the target’s appearance is changing due to its pose change. In case of target track loss, a search algorithm sweeps the space in vicinity of last target position to recover the lost target. A motion detection module used in our tracking system not only helps to initiate the tracking process automatically, it also finds the target’s presence after track loss. A fuzzy control is also synthesized to reach our control performance objectives. The idea is implemented in an active camera system to track moving targets. In addition, we've used the parallel processing technique for vision and control to reach acceptable speed and accuracy in real-time tracking.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Alireza Mustafa AU - Moteaal Asadi Shirzi AU - Muhammad Reza Hairi Yazdi PY - 2006/10 DA - 2006/10 TI - Active Tracking Using Kernel-Based Vision Processor and Robust Fuzzy Control BT - 9th Joint International Conference on Information Sciences (JCIS-06) PB - Atlantis Press UR - https://doi.org/10.2991/jcis.2006.276 DO - https://doi.org/10.2991/jcis.2006.276 ID - Mustafa2006/10 ER -