From Event: SPIE Commercial + Scientific Sensing and Imaging, 2017
Object tracking is a very important problem in computer vision research. Among the difficulties of object tracking, partial occlusion problem is one of the most serious and challenging problems. To address the problem, we proposed novel approaches to object tracking on plenoptic image sequences. Our approaches take advantage of the refocusing capability that plenoptic images provide. Our approaches input the sequences of focal stacks constructed from plenoptic image sequences. The proposed image selection algorithms select the sequence of optimal images that can maximize the tracking accuracy from the sequence of focal stacks. Focus measure approach and confidence measure approach were proposed for image selection and both of the approaches were validated by the experiments using thirteen plenoptic image sequences that include heavily occluded target objects. The experimental results showed that the proposed approaches were satisfactory comparing to the conventional 2D object tracking algorithms.
Jae Woo Kim, Seong-Joon Bae, Seongjin Park, and Do Hyung Kim, "Object tracking using plenoptic image sequences," Proc. SPIE 10219, Three-Dimensional Imaging, Visualization, and Display 2017, 1021909 (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 10, 2017; Published: 10 May 2017); https://doi.org/10.1117/12.2264431.
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