Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation from motion of non-rigid objects by neuronal lateral interaction
Pattern Recognition Letters
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Tracking Multiple Humans in Complex Situations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cast shadow detection in video segmentation
Pattern Recognition Letters
A shadow elimination approach in video-surveillance context
Pattern Recognition Letters
Motion features to enhance scene segmentation in active visual attention
Pattern Recognition Letters
Parametric model-based motion segmentation using surface selection criterion
Computer Vision and Image Understanding
Moving vehicles segmentation based on Bayesian framework for Gaussian motion model
Pattern Recognition Letters
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Automatic video segmentation using genetic algorithms
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Visual surveillance by dynamic visual attention method
Pattern Recognition
Object segmentation using ant colony optimization algorithm and fuzzy entropy
Pattern Recognition Letters
Centre of mass model - A novel approach to background modelling for segmentation of moving objects
Image and Vision Computing
A new video segmentation method of moving objects based on blob-level knowledge
Pattern Recognition Letters
Optimizing parameters of a motion detection system by means of a distributed genetic algorithm
Image and Vision Computing
Moving object segmentation by background subtraction and temporal analysis
Image and Vision Computing
Genetic algorithms for video segmentation
Pattern Recognition
Accumulative computation method for motion features extraction in active selective visual attention
WAPCV'04 Proceedings of the Second international conference on Attention and Performance in Computational Vision
Real-time motion detection by lateral inhibition in accumulative computation
Engineering Applications of Artificial Intelligence
Human activity monitoring by local and global finite state machines
Expert Systems with Applications: An International Journal
| Hi-index | 0.01 |
Segmentation of moving objects is an essential component of any vision system. However, its accomplishment is hard due to some challenges such as the occlusion treatment or the detection of objects with deformable appearance. In this paper an artificial neuronal network approach for moving object segmentation, called lateral interaction in accumulative computation (LIAC), which uses accumulative computation and recurrent lateral interaction is revisited. Although the results reported for this approach so far may be considered relevant, the problems faced each time (environment, objects of interest, etc.) make that the system outcome varies. Hence, our aim is to improve segmentation provided by LIAC in a double sense: by removing the detected objects not matching some size or compactness constraints, and by learning suitable parameters that improve the segmentation behavior through a genetic algorithm.