Artificial Intelligence
From image sequences towards conceptual descriptions
Image and Vision Computing
Neural mechanisms for the robust representation of junctions
Neural Computation
One-Shot Learning of Object Categories
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Object Recognition with Cortex-Like Mechanisms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video understanding for complex activity recognition
Machine Vision and Applications
A stochastic grammar of images
Foundations and Trends® in Computer Graphics and Vision
On scene interpretation with description logics
Image and Vision Computing
Ontology based complex object recognition
Image and Vision Computing
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Biologically inspired mobile robot vision localization
IEEE Transactions on Robotics
Learning the Compositional Nature of Visual Object Categories for Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Autonomous Mental Development
Mapping a Suburb With a Single Camera Using a Biologically Inspired SLAM System
IEEE Transactions on Robotics
Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision?
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Building a general-purpose, real-time active vision system completely based on biological models is a great challenge. We apply a number of biologically plausible algorithms which address different aspects of vision, such as edge and keypoint detection, feature extraction, optical flow and disparity, shape detection, object recognition and scene modelling into a complete system. We present some of the experiments from our ongoing work, where our system leverages a combination of algorithms to solve complex tasks.