Active vision
Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
Robot grasp synthesis algorithms: a survey
International Journal of Robotics Research
Transfer of Fixation Using Affine Structure: Extending theAnalysis to Stereo
International Journal of Computer Vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sensor planning for 3D object search
Computer Vision and Image Understanding
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Real-Time Epipolar Geometry Estimation of Binocular Stereo Heads
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
A Context-Dependent Attention System for a Social Robot
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Stochastic Guided Search Model for Search Asymmetries in Visual Search Tasks
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Control Basis for Haptically-Guided Grasping and Manipulation
A Control Basis for Haptically-Guided Grasping and Manipulation
Models of bottom-up and top-down visual attention
Models of bottom-up and top-down visual attention
Object Detection using Background Context
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Integrating context-free and context-dependent attentional mechanisms for gestural object reference
Machine Vision and Applications
VOCUS: A Visual Attention System for Object Detection and Goal-Directed Search (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)
Initialization and System Modeling in 3-D Pose Tracking
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Robotics and Autonomous Systems
Integration of visual and shape attributes for object action complexes
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Salient region detection using weighted feature maps based on the human visual attention model
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Learning visually guided grasping: a test case in sensorimotor learning
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Computational visual attention systems and their cognitive foundations: A survey
ACM Transactions on Applied Perception (TAP)
Interactive object recognition using proprioceptive and auditory feedback
International Journal of Robotics Research
A probabilistic framework for object search with 6-DOF pose estimation
International Journal of Robotics Research
Manipulator and object tracking for in-hand 3D object modeling
International Journal of Robotics Research
BADGr-A toolbox for box-based approximation, decomposition and GRasping
Robotics and Autonomous Systems
Proceedings of the Symposium on Eye Tracking Research and Applications
Design of a flexible tactile sensor for classification of rigid and deformable objects
Robotics and Autonomous Systems
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The ability to autonomously acquire new knowledge through interaction with the environment is an important research topic in the field of robotics. The knowledge can only be acquired if suitable perceptionâ聙聰 action capabilities are present: a robotic system has to be able to detect, attend to and manipulate objects in its surrounding. In this paper, we present the results of our long-term work in the area of vision-based sensing and control. The work on finding, attending, recognizing and manipulating objects in domestic environments is studied. We present a stereo-based vision system framework where aspects of top-down and bottom-up attention as well as foveated attention are put into focus and demonstrate how the system can be utilized for robotic object grasping.