Depth Estimation from Image Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Robust Tracking and Stereo Matching under Variable Illumination
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Reconstructing Occluded Surfaces Using Synthetic Apertures: Stereo, Focus and Robust Measures
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Robust Pose Estimation from a Planar Target
IEEE Transactions on Pattern Analysis and Machine Intelligence
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
A Probabilistic Cascade of Detectors for Individual Object Recognition
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Simultaneous Visual Object Recognition and Position Estimation Using SIFT
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
The Vision System of the ACROBOTER Project
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
Real-time camera pose in a room
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
| Hi-index | 0.00 |
Recent advances in mechanical and electronic engineering led to the building of more sophisticated mechatronic systems excelling in simplicity, reliability and versatility. On the contrary, the complexity of their parts necessitate integrated control systems along with advanced visual feedback. Generally, a vision system aims at bridging the gap between humans and machines in terms of providing to the latter information about what is perceived visually. This paper shows how the vision system of an advanced mechatronic framework named ACROBOTER is used for the localization of objects. ACROBOTER develops a new locomotion technology that can effectively be utilized in a workplace environment for manipulating small objects simultaneously. Its vision system is based on a multi-camera framework that is responsible for both finding patterns and providing their location in the 3D working space. Moreover, this work presents a novel method for recognizing objects in a scene and providing their spatial information.