Since then, this algorithm has been used, studied, and further developed by a number of researchers, such as in [26], Han et al. have used it for object tracking.
Geodesic methods do not depend on the type of movement and shape of the object, therefore they are used frequently for object tracking.
For example, in Smal et al. 2008; a particle filter tracker is used for multiple object tracking, although conventional particle filter trackers have often been developed for single object tracking.
However, the functionality of these sensors is limited only to the object identification and they are difficult to be used for the object tracking [10 12].
This section describes the proposed MAPF used for visual object tracking in complex dynamics, including the template model of the tracked objects (bounding rectangular model and circular model), and the proposed motion-adaptive model.
Several techniques based on particle filtering are used for multiple object tracking by the acoustic sensor, and the limitations of the acoustic sensor are discussed to identify the need for the visual sensor cooperation.
Section 2 summarizes related methods used for visual object tracking; Section 3 deals with the MAPF; Section 4 introduces experimental results and makes comparisons with the Continuously Adaptive Mean-shift (CAM-Shift) [21], standard PF [6], VAPF [15, 16], and M-PF [18]; and Section 5 outlines the conclusions and suggestions for future research.
Therefore, this algorithm can be used as a proper method for object tracking based on color feature.
A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed.
A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach was proposed for object tracking using multiple cameras.
