Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
On the relative complexity of active vs. passive visual search
International Journal of Computer Vision
Controlling eye movements with hidden Markov models
International Journal of Computer Vision
CVGIP: Image Understanding - Special issue on purposive, qualitative, active vision
Control of selective perception using Bayes nets and decision theory
International Journal of Computer Vision - Special issue on active vision II
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
Control of a Camera for Active Vision: Foveal Vision, Smooth Tracking and Saccade
International Journal of Computer Vision - Special issue on computer vision research at the Technion
Active Robot Vision: Camera Heads, Model Based Navigation and Reactive Control
Active Robot Vision: Camera Heads, Model Based Navigation and Reactive Control
Motion Understanding: Task-Directed Attention and Representations that Link Perception with Action
International Journal of Computer Vision
Object-based Visual Attention: a Model for a Behaving Robot
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Attention-Based Dynamic Visual Search Using Inner-Scene Similarity: Algorithms and Bounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
APES: Attentively Perceiving Robot
Autonomous Robots
2006 Special Issue: Modeling attention to salient proto-objects
Neural Networks
Computational visual attention systems and their cognitive foundations: A survey
ACM Transactions on Applied Perception (TAP)
Bubble space and place representation in topological maps
International Journal of Robotics Research
Integrating cue descriptors in bubble space for place recognition
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
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An attentive robot needs to exhibit a plethora of different visual behaviors including free viewing, detecting visual onsets, search, remaining fixated and tracking depending on the vision task at hand. The robot's associated camera movements--ranging from saccades to smooth pursuit--direct its optical axis in a manner that is dependent on the current visual behavior. This paper proposes a closed-loop dynamical systems approach to the generation of camera movements based on a family of artificial potential functions. Each movement from the current fixation point to the next is associated with an artificial potential function that encodes saliency and possibly inhibition depending on the visual behavior that the robot is engaged in. The novelty of this approach is that since the nature of resulting motion can vary from being saccadic to smooth pursuit, the full repertoire of visual behaviors all become possible within the same framework. The robot can switch its visual behavior simply by changing the parameters of the constructed artificial potential functions appropriately. Furthermore, automated reflexive changes among the different visual behaviors can be achieved via a simple switching automaton. Experimental results with APES robot serve to show the performance properties of a robot engaged in each different visual behavior.