Robust Object Tracking in Infrared Video via Particle Filters
| Autor: | Claudio Delrieux, Adrián Stácul, Edgardo Comas |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer engineering. Computer hardware
Similarity (geometry) Positioning system Computer science 02 engineering and technology Image Analysis Pattern Recognition Tracking (particle physics) 01 natural sciences Image analysis 010309 optics TK7885-7895 0203 mechanical engineering Pattern recognition Particle filter 0103 physical sciences Computer vision 020301 aerospace & aeronautics business.industry Tracking Particle Filter QA75.5-76.95 Object (computer science) Filter (video) Feature (computer vision) Video tracking Electronic computers. Computer science Computer Vision and Pattern Recognition Artificial intelligence business Software |
| Zdroj: | ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 19, Iss 1 (2020) Dipòsit Digital de Documents de la UAB Universitat Autònoma de Barcelona |
| ISSN: | 1577-5097 |
| Popis: | In this paper we investigate the effectiveness of particle filters for object tracking in infrared videos. Once the user identifies the target object to be followed in position and size, its most representative feature points are obtained by means of the SURF algorithm. A particle filter is initialized with these feature points, and the location of the object within the video frames is determined by the average value of the particles that have a greater similarity with the target. Two different field tests were carried out to study the filter behaviour in comparison with previously used methods in the bibliography. The first one was tracking an unmanned aerial vehicle (UAV) in the open. The second one was to identify a heliport in a noisy infrared zenithal video take. In the first test, the UAV was followed by another positioning system simultaneously, thus allowing the comparison of both systems, and the evaluation in the improvement introduced by the particle algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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