Different from traditional point target tracking systems assuming that a target generates at most one single measurement per scan, there exists a class of multipath target tracking systems where each measurement may originate from the interested target via one of multiple propagation paths or from clutter, while the correspondence among targets, measurements, and propagation paths is unknown. T...

This work presents two main contributions to achieve robust multiple-target tracking in uncontrolled scenarios. A novel system which consists on a hierarchical architecture is proposed. Each level is devoted to one of the main tracking functionalities: target detection, low-level tracking, and high-level tasks such as target-appearance representation, or event management. Secondly, tracking per...

More measurements are generated by the target per observation interval, when the target is detected by a high resolution sensor, or there are more measurement sources on the target surface. Such a target is referred to as an extended target. The probability hypothesis density filter is considered an efficient method for tracking multiple extended targets. However, the crucial problem of how to ...

The decision-based models for maneuvering target tracking were studied in this paper. Focusing on the problem of dissatisfied with single model tracking and the optimal model-set is difficult to design of the multiple-model (MM) algorithm, we modified the “current” model, and proposed an adaptive single model (ASM) to track angular motion. The united velocity-acceleration estimation-based and d...

Successful multi-target tracking requires locating the targets and labeling their identities. This mission becomes significantly more challenging when many targets frequently interact with each other (present partial or complete occlusions). This paper presents an on-line supervised learning based method for tracking multiple interacting targets. When the targets do not interact with each other...

In this paper the Multiple Hypothesis Tracking with group tracking is applied to tracking targets in video sequences. The width/height ratio is used as a target feature to help in target/detection association. Group tracking is tested in real video sequences (PETS 2001) and shows that is possible to keep linked the otherwise interrupted tracks.

A key element for successful tracking is knowing from which target each measurement originates. These measurement-to-target associations are generally unavailable, and the tracking problem becomes one of estimating both the assignments and the target states. We present the Probabilistic Least Squares Tracking (msPLST) algorithm for estimating the measurement-to-target assignments and the track ...