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ICPR
2000
IEEE
16 years 5 months ago
Mixture Densities for Video Objects Recognition
The appearance of non-rigid objects detected and tracked in video streams is highly variable and therefore makes the identification of similar objects very complex. Furthermore, i...
Riad I. Hammoud, Roger Mohr
GECCO
2003
Springer
126views Optimization» more  GECCO 2003»
15 years 9 months ago
Coevolution and Linear Genetic Programming for Visual Learning
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
Krzysztof Krawiec, Bir Bhanu
ICRA
2005
IEEE
105views Robotics» more  ICRA 2005»
15 years 9 months ago
A New Approach to the Use of Edge Extremities for Model-based Object Tracking
— This paper presents a robust model-based visual tracking algorithm that can give accurate 3D pose of a rigid object. Our tracking algorithm uses an incremental pose update sche...
Youngrock Yoon, Akio Kosaka, Jae Byung Park, Avina...
ICCS
2005
Springer
15 years 9 months ago
A Comparative Study of Acceleration Techniques for Geometric Visualization
Abstract. Nowadays computer graphics hardware presents a series of characteristics, such as AGP memory, vertex cache, etc., that can be used for real-time rendering. The aim of thi...
Pascual Castelló, J. Francisco Ramos, Migue...
ESANN
2006
15 years 5 months ago
Learning Visual Invariance
Invariance is a necessary feature of a visual system able to recognize real objects in all their possible appearance. It is also the processing step most problematic to understand ...
Alessio Plebe