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- W4380087865 abstract "This chapter deals with an application of visual object tracking. The algorithm is detecting and following a human in real time, while overcoming all the practical challenges: brusque object motion, pose variation, non-rigid object structure, full/partial occlusion, and smooth/abrupt camera motion. A critical scrutiny of the efficacy of human tracking algorithms by analyzing assorted visual parameters has been done. This work proposes a novel implementation of the GRABCUT algorithm on interest point-based method. This region growing algorithm eliminates the background descriptors from the object model and this information is used by a SURF-based tracker. Later to differentiate between pose change and occlusion situation an auto-tuned classifier is implemented. The algorithm developed in this chapter is adaptive, robust, and computable in real time. The experiments are conducted in indoor/outdoor environments." @default.
- W4380087865 created "2023-06-10" @default.
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- W4380087865 date "2023-01-01" @default.
- W4380087865 modified "2023-09-27" @default.
- W4380087865 title "A Solution to Pose Change Challenge: Real-Time, Robust, and Adaptive Human Tracking Systems Using SURF" @default.
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- W4380087865 doi "https://doi.org/10.1007/978-3-031-23602-0_7" @default.
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