A Novel Object Tracking Algorithm By Fusing Color And Depth Information Based On Single Valued Neutrosophic Cross Entropy
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A novel object tracking algorithm by fusing color and depth information based on single valued neutrosophic cross-entropy
Although appearance based trackers have been greatly improved in the last decade, they are still struggling with some challenges like occlusion, blur, fast motion, deformation, etc. As known, occlusion is still one of the soundness challenges for visual tracking. Other challenges are also not fully resolved for the existed trackers. In this work, we focus on tackling the latter problem in both color and depth domains.
A novel object tracking algorithm by fusing color and depth information based on single valued neutrosophic cross-entropy
Although appearance based trackers have been greatly improved in the last decade, they are still struggling with some challenges like occlusion, blur, fast motion, deformation, etc. As known, occlusion is still one of the soundness challenges for visual tracking. Other challenges are also not fully resolved for the existed trackers. In this work, we focus on tackling the latter problem in both color and depth domains.
Neutrosophic Hough Transform-Based Track Initiation Method for Multiple Target Tracking
A neutrosophic Hough transform-based track initiation method (NHT-TI) is proposed to solve the uncertain track initiation problem in a complex surveillance environment. In the proposed method, a neutrosophic set is employed to describe the uncertain association of a measurement with different targets, which is divided into three categories including the association with real targets, uncertain targets and false targets,respectively.