Embedded real-time people detection and tracking with time-of-flight camera

Levente Tamas; Andrei Cozma

doi:10.1117/12.2586057

12 April 2021 Embedded real-time people detection and tracking with time-of-flight camera

Levente Tamas, Andrei Cozma

Proceedings Volume 11736, Real-Time Image Processing and Deep Learning 2021; 117360B (2021) https://doi.org/10.1117/12.2586057
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

People recognition is a relevant subset of the generic image based recognition task with many possible application areas such as security, surveillance, human-robot interaction or recently the social security in a pandemic context. In this work we present a light-weight recognition pipeline for time-of-flight cameras based on deep learning techniques tailored to this specific type of camera with registered infrared and depth images. By combining the maturity of the 2D image based recognition techniques with the custom depth sensing we achieved effective solutions for a number of relevant industrial applications. In particular, our focus was on automatic door-control and people counting applications.

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Citation Download Citation

Levente Tamas and Andrei Cozma "Embedded real-time people detection and tracking with time-of-flight camera", Proc. SPIE 11736, Real-Time Image Processing and Deep Learning 2021, 117360B (12 April 2021); https://doi.org/10.1117/12.2586057

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