Title :
CMOS dynamic linking networks for real-time human face tracking
Author_Institution :
Analog & Mixed-Signal Center, Texas A&M Univ., College Station, TX, USA
Abstract :
Dynamic linking networks are very effective in locating human faces, as they are invariant to changes in position, orientation, scale, deformation, and partial lighting. Additionally, these networks are well suited for analog VLSI using very simple CMOS circuits such as programmable ring oscillators, strongly coupled diffusion lattices, and AC-coupled Hebbian synapses. Dynamic linking networks are orders of magnitude faster than digital computers, thus they provide a fast, efficient, and robust means of tracking faces in real-time. Transistor-level simulation results are presented for the .5 μm TSMC CMOS technology with 3-volt supply
Keywords :
CMOS analogue integrated circuits; Hebbian learning; VLSI; analogue processing circuits; face recognition; feature extraction; neural chips; real-time systems; 0.5 micron; 3 V; AC-coupled Hebbian synapses; CMOS dynamic linking networks; TSMC CMOS technology; analog VLSI; deformation; orientation; partial lighting; position; programmable ring oscillators; real-time human face tracking; scale; strongly coupled diffusion lattices; transistor-level simulation results; CMOS analog integrated circuits; CMOS technology; Computer networks; Coupling circuits; Face; Humans; Joining processes; Lattices; Ring oscillators; Very large scale integration;
Conference_Titel :
Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
Conference_Location :
Geneva
Print_ISBN :
0-7803-5482-6
DOI :
10.1109/ISCAS.2000.857122