Paper Info
Title
VLSI neuroprocessors for video motion detection.
Abstract
The system design of a locally connected competitive neural network for video motion detection is presented. The motion information from a sequence of image data can be determined through a two-dimensional multiprocessor array in which each processing element consists of an analog neuroprocessor. Massively parallel neurocomputing is done by compact and efficient neuroprocessors. Local data transfer between the neuroprocessors is performed by using an analog point-to-point interconnection scheme. To maintain strong signal strength over the whole system, global data communication between the host computer and neuroprocessors is carried out in a digital common bus. A mixed-signal very large scale integration (VLSI) neural chip that includes multiple neuroprocessors for fast video motion detection has been developed. Measured results of the programmable synapse, and winner-takes-all circuitry are presented. Based on the measurement data, system-level analysis on a sequence of real-world images was conducted.
Year
DOI
Venue
1993
10.1109/72.207607
IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council
Keywords
Field
DocType
video motion detection,vlsi neuroprocessors,parallel processing,locally connected competitive neural network,vlsi,2d multiprocessor array,motion estimation,winner-takes-all circuitry,image sequences,digital common bus,analog point-to-point interconnection scheme,signal detection,video signals,neural chips,data transfer,programmable synapse
Data transmission,Massively parallel,Computer science,Artificial intelligence,Motion estimation,Computer hardware,Artificial neural network,Very-large-scale integration,Pattern recognition,Motion detection,Chip,Host (network),Embedded system
Journal
Volume
Issue
ISSN
4
2
1045-9227
Citations 
PageRank 
References 
4
0.69
9
Authors
4
Name
Order
Citations
PageRank
J. -C. Lee140.69
B. J. Sheu212928.40
W. -C. Fang340.69
Chellappa, R.4130501440.56