Title :
A biologically inspired modular VLSI system for visual measurement of self-motion
Author :
Higgins, Charles M. ; Shams, Shaikh Arif
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Arizona, Tucson, AZ, USA
fDate :
12/1/2002 12:00:00 AM
Abstract :
We introduce a biologically inspired computational architecture for small-field detection and wide-field spatial integration of visual motion based on the general organizing principles of visual motion processing common to organisms from insects to primates. This highly parallel architecture begins with two-dimensional (2-D) image transduction and signal conditioning, performs small-field motion detection with a number of parallel motion arrays, and then spatially integrates the small-field motion units to synthesize units sensitive to complex wide-field patterns of visual motion. We present a theoretical analysis demonstrating the architecture´s potential in discrimination of wide-field motion patterns such as those which might be generated by self-motion. A custom VLSI hardware implementation of this architecture is also described, incorporating both analog and digital circuitry. The individual custom VLSI elements are analyzed and characterized, and system-level test results demonstrate the ability of the system to selectively respond to certain motion patterns, such as those that might be encountered in self-motion, at the exclusion of others.
Keywords :
CMOS image sensors; CMOS integrated circuits; VLSI; computer vision; image processing equipment; image sequences; mixed analogue-digital integrated circuits; motion estimation; parallel architectures; 2D image transduction; CMOS MOSIS chip; address event representation; analog circuitry; biologically inspired computational architecture; biologically inspired modular VLSI system; complex wide-field patterns; custom VLSI hardware implementation; digital circuitry; highly parallel architecture; parallel motion arrays; self-motion; signal conditioning; small-field detection; small-field motion detection; visual measurement; wide-field spatial integration; Biology computing; Computer architecture; Insects; Motion analysis; Motion detection; Organisms; Organizing; Parallel architectures; Pattern analysis; Very large scale integration;
Journal_Title :
Sensors Journal, IEEE
DOI :
10.1109/JSEN.2002.807304