Depth estimation is crucial in several computer vision applications, and a recent trend aims at inferring such a cue from a single camera through computationally demanding CNNs - precluding their practical deployment in several application contexts characterized by low-power constraints. Purposely, we develop a tiny network tailored to microcontrollers, processing low-resolution images to obtain a coarse depth map of the observed scene. Our solution enables depth perception with minimal power requirements (a few hundreds of mW), accurately enough to pave the way to several high-level applications at-the-edge.
Enabling monocular depth perception at the very edge / Peluso, V.; Cipolletta, A.; Calimera, A.; Poggi, M.; Tosi, F.; Aleotti, F.; Mattoccia, S.. - 2020(2020), pp. 1581-1583. ((Intervento presentato al convegno 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 tenutosi a usa nel 2020.
Titolo: | Enabling monocular depth perception at the very edge |
Autori: | |
Data di pubblicazione: | 2020 |
Abstract: | Depth estimation is crucial in several computer vision applications, and a recent trend aims at i...nferring such a cue from a single camera through computationally demanding CNNs - precluding their practical deployment in several application contexts characterized by low-power constraints. Purposely, we develop a tiny network tailored to microcontrollers, processing low-resolution images to obtain a coarse depth map of the observed scene. Our solution enables depth perception with minimal power requirements (a few hundreds of mW), accurately enough to pave the way to several high-level applications at-the-edge. |
ISBN: | 978-1-7281-9360-1 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2851214