Vision and navigation for the Carnegie-Mellon navlab
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Artificial Intelligence
Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Context-based vision system for place and object recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Swarm-Based Volition/Attention Framework for Object Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
An agent based evolutionary approach to path detection for off-road vehicle guidance
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Off-road Path Following using Region Classification and Geometric Projection Constraints
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Emergence of attention within a neural population
Neural Networks
Particle Swarms as Video Sequence Inhabitants For Object Tracking in Computer Vision
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Stanley: The robot that won the DARPA Grand Challenge: Research Articles
Journal of Robotic Systems - Special Issue on the DARPA Grand Challenge, Part 2
2006 Special Issue: Modeling attention to salient proto-objects
Neural Networks
Reverse Optical Flow for Self-Supervised Adaptive Autonomous Robot Navigation
International Journal of Computer Vision
A Multi-agent Approach for Range Image Segmentation
CEEMAS '07 Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V
Real-time outdoor trail detection on a mobile robot
RA '07 Proceedings of the 13th IASTED International Conference on Robotics and Applications
Appearance contrast for fast, robust trail-following
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Terrain-based sensor selection for autonomous trail following
RobVis'08 Proceedings of the 2nd international conference on Robot vision
A swarm cognition realization of attention, action selection, and spatial memory
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Goal-directed search with a top-down modulated computational attention system
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
An evolutionary autonomous agents approach to image featureextraction
IEEE Transactions on Evolutionary Computation
Tracking natural trails with swarm-based visual saliency
Journal of Field Robotics
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This paper extends an existing saliency-based model for path detection and tracking so that the appearance of the path being followed can be learned and used to bias the saliency computation process. The goal is to reduce ambiguities in the presence of strong distractors. In both original and extended path detectors, neural and swarm models are layered in order to attain a hybrid solution. With generalisation to other tasks in mind, these detectors are presented as instances of a generic neural-swarm layered architecture for visual saliency computation. The architecture considers a swarm-based substrate for the extraction of high-level perceptual representations, given the low-level perceptual representations extracted by a neural-based substrate. The goal of this division of labour is to ensure parallelism across the vision system while maintaining scalability and tractability. The proposed model is shown to exhibit, at 20Hz, a 98.67% success rate on a diverse data-set composed of 39 videos encompassing a total of 29,789 640x480 frames. An open source implementation of the model, fully encapsulated as a node of the Robotics Operating System (ROS), is available for download.