Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
Active object recognition integrating attention and viewpoint control
Computer Vision and Image Understanding
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous Localization and Map-Building Using Active Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Playing Domino: A Case Study for an Active Vision System
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
Object-based visual attention for computer vision
Artificial Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Integrating context-free and context-dependent attentional mechanisms for gestural object reference
Machine Vision and Applications
A model of active visual search with object-based attention guiding scan paths
Neural Networks - 2004 Special issue Vision and brain
A Principled Approach to Detecting Surprising Events in Video
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
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
VOCUS: A Visual Attention System for Object Detection and Goal-Directed Search (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)
A Behavioral Analysis of Computational Models of Visual Attention
International Journal of Computer Vision
A distributed model of spatial visual attention
Biomimetic Neural Learning for Intelligent Robots
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Bottom-Up Gaze Shifts and Fixations Learning by Imitation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Developmental Roadmap for Learning by Imitation in Robots
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Active vision for sociable robots
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Development of a biologically inspired real-time spatiotemporal visual attention system
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
SIFT on manifold: An intrinsic description
Neurocomputing
Hi-index | 0.00 |
Visual attention is one of the major requirements for a robot to serve as a cognitive companion for human. The robotic visual attention is mostly concerned with overt attention which accompanies head and eye movements of a robot. In this case, each movement of the camera head triggers a number of events, namely transformation of the camera and the image coordinate systems, change of content of the visual field, and partial appearance of the stimuli. All of these events contribute to the reduction in probability of meaningful identification of the next focus of attention. These events are specific to overt attention with head movement and, therefore, their effects are not addressed in the classical models of covert visual attention. This paper proposes a Bayesian model as a robot-centric solution for the overt visual attention problem. The proposed model, while taking inspiration from the primates visual attention mechanism, guides a robot to direct its camera toward behaviorally relevant and/or visually demanding stimuli. A particle filter implementation of this model addresses the challenges involved in overt attention with head movement. Experimental results demonstrate the performance of the proposed model.