Analog VLSI implementation of spatio-temporal frequency tuned visual motion algorithms

• Published in: IEEE transactions on circuits and systems. I, Regular papers Vol. 52; no. 3; pp. 489 - 502
• Main Authors: Higgins, C.M., Pant, V., Deutschmann, R.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2005; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Analog very large-scale integration (VLSI); biomimetic; Circuit design; Circuit synthesis; Energy consumption; Focal plane; Frequency measurement; Hardware; Integrated circuits; Large scale integration; MOSFET circuits; Motion measurement; Motion sensors; R&D; Research & development; Sensor arrays; Sensor phenomena and characterization; Sensors; spatio-temporal frequency; Very large scale integration; vision chip; Visual
• ISSN: 1549-8328; 1558-0806
• DOI: 10.1109/TCSI.2004.841601

The computation of local visual motion can be accomplished very efficiently in the focal plane with custom very large-scale integration (VLSI) hardware. Algorithms based on measurement of the spatial and temporal frequency content of the visual motion signal, since they incorporate no thresholding operation, allow highly sensitive responses to low contrast and low-speed visual motion stimuli. We describe analog VLSI implementations of the three most prominent spatio-temporal frequency-based visual motion algorithms, present characterizations of their performance, and compare the advantages of each on an equal basis. This comparison highlights important issues in the design of analog VLSI sensors, including the effects of circuit design on power consumption, the tradeoffs of subthreshold versus above-threshold MOSFET biasing, and methods of layout for focal plane vision processing arrays. The presented sensors are capable of distinguishing the direction of motion of visual stimuli to less than 5% contrast, while consuming as little as 1 /spl mu/W of electrical power. These visual motion sensors are useful in embedded applications where minimum power consumption, size, and weight are crucial.