Title :
Retrieving gray-level information from a Binary Sensor and its application to gesture detection
Author :
Orazio Gallo;Iuri Frosio;Leonardo Gasparini;Kari Pulli;Massimo Gottardi
Author_Institution :
NVIDIA, Santa Clara, California, United States
fDate :
6/1/2015 12:00:00 AM
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.
Keywords :
"Power demand","Kernel","Lighting","Dynamic range","IP networks","Training","Data mining"
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2015 IEEE Conference on
Electronic_ISBN :
2160-7516
DOI :
10.1109/CVPRW.2015.7301362