<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Nowadays, research in area of intelligent transportation system is focused on analysis of traffic flow by computer vision techniques. Keypoint analysis represents detection, modelling and recognition of objects in traffic flow and object tracking as well. The main goal of this paper is to propose new approach to detect and modelling 3D objects that move on road surface. At the beginning, basic methods of object recognition and modelling of 3D object are shortly described. The modified algorithm based on background subtraction and creation of 3D model by depth map is proposed. Finally, the results of developed algorithm are depicted through the last part of this paper.</p></abstract>

Nowadays, research in area of intelligent transportation system is focused on analysis of traffic flow by computer vision techniques. Keypoint analysis represents detection, modelling and recognition of objects in traffic flow and object tracking as well. The main goal of this paper is to propose new approach to detect and modelling 3D objects that move on road surface. At the beginning, basic methods of object recognition and modelling of 3D object are shortly described. The modified algorithm based on background subtraction and creation of 3D model by depth map is proposed. Finally, the results of developed algorithm are depicted through the last part of this paper.

Local Feature Extraction in the Near Infra-Red Domain for Wildlife Mammals Tracking Purpose

Department of Telecommunications and Multimedia, Faculty of Electrical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia.

Civil and Environmental Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Nowadays, research in area of intelligent transportation system is focused on analysis of traffic flow by computer vision techniques. Keypoint analysis...

Local Feature Extraction in the Near Infra-Red Domain for Wildlife Mammals Tracking Purpose

Published Online: May 12, 2016

Page range: 34 - 41

DOI: https://doi.org/10.1515/cee-2016-0005

Keywords
Intelligent transportation system, Animal detection, Object recognition, Infrared domain, Local feature extraction

© 2016 Tibor Trnovszký et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Local Feature Extraction in the Near Infra-Red Domain for Wildlife Mammals Tracking Purpose

Published Online: May 12, 2016

Page range: 34 - 41

DOI: https://doi.org/10.1515/cee-2016-0005

KeywordsIntelligent transportation system, Animal detection, Object recognition, Infrared domain, Local feature extraction

© 2016 Tibor Trnovszký et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Intelligent transportation system, Animal detection, Object recognition, Infrared domain, Local feature extraction