IEEE Transactions on Pattern Analysis and Machine Intelligence
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Structure from motion using line correspondences
International Journal of Computer Vision
Computing minimal surfaces via level set curvature flow
Journal of Computational Physics
Journal of Computational Physics
Journal of Computational Physics
Randomized polygon search for planar motion detection
Pattern Recognition Letters
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Level set methods for curvature flow, image enhancement, and shape recovery in medical images
Visualization and mathematics
Detection of independent motion using directional motion estimation
Computer Vision and Image Understanding
Image object signatures from centripetal autowaves
Pattern Recognition Letters
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Processing Using Pulse-Coupled Neural Networks
Image Processing Using Pulse-Coupled Neural Networks
Perceptual organization based computational model for robust segmentation of moving objects
Computer Vision and Image Understanding
Using Adaptive Tracking to Classify and Monitor Activities in a Site
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Guest Editorial Overview Of Pulse Coupled Neural Network (PCNN) Special Issue
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Emergent synchrony in locally coupled neural oscillators
IEEE Transactions on Neural Networks
Review article: Review of pulse-coupled neural networks
Image and Vision Computing
Review: Pulse coupled neural networks and its applications
Expert Systems with Applications: An International Journal
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The intersecting cortical model (ICM) is a model based on neural network techniques especially designed for image processing. It was derived from several visual cortex models and is basically the intersection of these models, i.e. the common elements amongst these models. The theoretical foundation of the ICM is given and it is shown how the ICM can be derived as a reduced set of equations of the pulse-coupled neural network based upon models proposed by Eckhorn and Reitboeck.Tests of the ICM are presented: one on a series of images of an aircraft moving in the sky; two on car detection; and one on preparations of underground nuclear explosions.The ICM is shown here, in a few examples, to be useful in imagery change detection: aircraft moving against a homogeneous background without precise geometric matching; car on a road; two cars moving in an urban setting without precise geometric matching; and for a linear structure in a complex background. The ICM can be used when the moving objects are not too small and the background is not too difficult. Changes involving larger linear structures can be detected even if the background is not homogeneous.