Visual Object Tracking on Multi-modal RGB-D Videos: A Review
It provides a comprehensive overview for researchers working on object tracking in complex scenarios using multi-modal data, but it is incremental as it reviews existing work without introducing new methods.
This review paper summarizes the field of visual object tracking on RGB-D videos, covering benchmarking datasets, performance measurements, existing methods, and future directions.
The development of visual object tracking has continued for decades. Recent years, as the wide accessibility of the low-cost RGBD sensors, the task of visual object tracking on RGB-D videos has drawn much attention. Compared to conventional RGB-only tracking, the RGB-D videos can provide more information that facilitates objecting tracking in some complicated scenarios. The goal of this review is to summarize the relative knowledge of the research filed of RGB-D tracking. To be specific, we will generalize the related RGB-D tracking benchmarking datasets as well as the corresponding performance measurements. Besides, the existing RGB-D tracking methods are summarized in the paper. Moreover, we discuss the possible future direction in the field of RGB-D tracking.