Abstract
In this paper, an approach for identifying corresponding image features across different imaging modalities is presented. The method includes spatial alignment of sensor images on short and long distance as well as a probabilistic fusion approach for combining multiple unimodal to multimodal image features. An experimental statistical comparison of uni- and multimodal image features is performed using RGB, IR and thermal cameras. Therefore, the sensors are mounted on an Ackermann steering platform in a typical industrial environment. The multimodal features are examined regarding repetitive characteristics, quantity and spatial distribution.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
