1. [Publications](/publications)
2. Retrieving Gray-Level Information from a Binary Sensor and its Application to Gesture Detection
 
 # Retrieving Gray-Level Information from a Binary Sensor and its Application to Gesture Detection

  ![](/sites/default/files/styles/wide/public/pubs/2015-06_Retrieving-Gray-Level-Information/representative.jpg?itok=SJIKhBo9)

 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 150us 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.



 ## Authors



Orazio Gallo (NVIDIA)

[Iuri Frosio](/person/iuri-frosio)

Leonardo Gasparini (FBK)

Kari Pulli (Light)

Massimo Gottardi (FBK)

 

 

 ## Publication Date



Monday, June 1, 2015

 

 ## Published in



[IEEE Computer Vision and Pattern Recognition (CVPR 2015), Embedded Vision Works…](http://www.pamitc.org/cvpr15/)

 

 ## Research Area



[Computer Vision](/research-area/computer-vision)

 

 

 ## Uploaded Files



[GalloEtAl\_GrayHDR\_CVPRW15.pdf](https://research.nvidia.com/sites/default/files/pubs/2015-06_Retrieving-Gray-Level-Information/GalloEtAl_GrayHDR_CVPRW15.pdf "Open file in new window")1.46 MB

 

 

 ## Copyright



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