Sentence examples for multiple human tracking from inspiring English sources

However, the multi-way data associations are difficult to achieve real-time multiple human tracking.

According to our opinion, the mutual shielding effect is the crucial problem appearing in multiple human tracking [28 31].

However, the problem of multiple human tracking in a real complex environment has been less well addressed (e.g. [25]).

Based on different disposal method of the human objects' association, the joint multiple-human tracking can be divided into three categories, i.e., JPDAF, MHT, and FNF.

However, this method is difficult to deal with numerous targets and measurements such as multiple human objects tracking in crowded scenes.

To better deal with this issue to improve the robustness and effectiveness under occlusion further, Hou et al. [15, 16] propose a deformable multiple-kernel-based human tracking system using a moving camera.

To reduce the computational requirement, Zúñiga et al. [22] propose a real-time MHT-based multi-human tracking approach, which can reliably track multiple human objects even in noisy environments.

Fig. 8 Illustration of tracking multiple human targets in a crowded scene [21].

Fig. 6 Illustration of tracking multiple human targets in an outdoor scene.

Such an example of tracking multiple human targets in a crowded scene is shown in Fig. 8.

However, the proposed approach is difficult to select a criterion to partition human objects' sub-regions, especially when tracking multiple human objects.