Robot Person Following in Uniform Crowd Environment

• URL: http://arxiv.org/abs/2205.10553v1
• Date: Sat, 21 May 2022 10:20:14 GMT
• Title: Robot Person Following in Uniform Crowd Environment
• Authors: Adarsh Ghimire, Xiaoxiong Zhang, Sajid Javed, Jorge Dias, Naoufel Werghi
• Abstract summary: Person-tracking robots have many applications, such as in security, elderly care, and socializing robots. In this work, we focus on improving the perceptivity of a robot for a person following task by developing a robust and real-time applicable object tracker. We present a new robot person tracking system with a new RGB-D tracker, Deep Tracking with RGB-D (DTRD) that is resilient to tricky challenges introduced by the uniform crowd environment.
• Score: 13.708992331117281
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Person-tracking robots have many applications, such as in security, elderly care, and socializing robots. Such a task is particularly challenging when the person is moving in a Uniform crowd. Also, despite significant progress of trackers reported in the literature, state-of-the-art trackers have hardly addressed person following in such scenarios. In this work, we focus on improving the perceptivity of a robot for a person following task by developing a robust and real-time applicable object tracker. We present a new robot person tracking system with a new RGB-D tracker, Deep Tracking with RGB-D (DTRD) that is resilient to tricky challenges introduced by the uniform crowd environment. Our tracker utilizes transformer encoder-decoder architecture with RGB and depth information to discriminate the target person from similar distractors. A substantial amount of comprehensive experiments and results demonstrate that our tracker has higher performance in two quantitative evaluation metrics and confirms its superiority over other SOTA trackers.

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