Retrieving Gray-Level Information from a Binary Sensor and Its Application to Gesture Detection
Abstract
We report on the use of a CMOS Contrast-based Binary Vision Sensor (CBVS), with embedded contrast extraction, for gesture detection applications. The first advantage of using this sensor over commercial imagers is a dynamic range of 120dB, made possible by a pixel design that effectively performs auto-exposure control. Another benefit is that, by only delivering the pixels detecting a contrast, the sensor requires a very limited bandwidth. We leverage the sensor's fast 150μs readout speed, to perform multiple reads during a single exposure; this allows us to estimate gray-level information from the otherwise binary pixels. As a use case for this novel readout strategy, we selected in-car gesture detection, for which we carried out preliminary tests showing encouraging results.
Cite
Text
Gallo et al. "Retrieving Gray-Level Information from a Binary Sensor and Its Application to Gesture Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015. doi:10.1109/CVPRW.2015.7301362Markdown
[Gallo et al. "Retrieving Gray-Level Information from a Binary Sensor and Its Application to Gesture Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015.](https://mlanthology.org/cvprw/2015/gallo2015cvprw-retrieving/) doi:10.1109/CVPRW.2015.7301362BibTeX
@inproceedings{gallo2015cvprw-retrieving,
title = {{Retrieving Gray-Level Information from a Binary Sensor and Its Application to Gesture Detection}},
author = {Gallo, Orazio and Frosio, Iuri and Gasparini, Leonardo and Pulli, Kari and Gottardi, Massimo},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2015},
pages = {21-26},
doi = {10.1109/CVPRW.2015.7301362},
url = {https://mlanthology.org/cvprw/2015/gallo2015cvprw-retrieving/}
}