Advantages of Selective Change-Driven Vision for Resource-Limited Systems
ABSTRACT Selective change-driven (SCD) vision is a capture/processing strategy especially suited for vision systems with limited resources and/or vision applications with real-time constraints. SCD vision capture essentially involves delivering only the pixels that have undergone the greatest change in illumination since the last time they were read-out. SCD vision processing involves processing a limited pixel flow with similar results to the usual image flow, but with far lower bandwidth and processing requirements. SCD vision is based on pixel flow processing instead of traditional image flow processing. This complete change in the way video is processed and has a direct impact on the processing hardware required to deal with visual information. In this paper, we present the first CMOS sensor using the SCD strategy, along with a highly resource-limited system implementing an object tracking experiment. Results show that SCD vision outperforms traditional vision systems by at least one order of magnitude, with limited hardware requirements for the specific tracking experiment being tested.
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ABSTRACT: Selective change driven (SCD) Vision is a biologically inspired strategy for acquiring, transmitting and processing images that significantly speeds up image sensing. SCD vision is based on a new CMOS image sensor which delivers, ordered by the absolute magnitude of its change, the pixels that have changed after the last time they were read out. Moreover, the traditional full frame processing hardware and programming methodology has to be changed, as a part of this biomimetic approach, to a new processing paradigm based on pixel processing in a data flow manner, instead of full frame image processing.Sensors 12/2011; 11(11):11000-20. DOI:10.3390/s111111000 · 2.05 Impact Factor
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ABSTRACT: This article deals with the application of the principles of SCD (Selective Change Driven) vision to 3D laser scanning. Two experimental sets have been implemented: one with a classical CMOS (Complementary Metal-Oxide Semiconductor) sensor, and the other one with a recently developed CMOS SCD sensor for comparative purposes, both using the technique known as Active Triangulation. An SCD sensor only delivers the pixels that have changed most, ordered by the magnitude of their change since their last readout. The 3D scanning method is based on the systematic search through the entire image to detect pixels that exceed a certain threshold, showing the SCD approach to be ideal for this application. Several experiments for both capturing strategies have been performed to try to find the limitations in high speed acquisition/processing. The classical approach is limited by the sequential array acquisition, as predicted by the Nyquist.Sensors 10/2013; 13(10):13143-13162. DOI:10.3390/s131013143 · 2.05 Impact Factor