Fast Vehicle Detection based on Haarlike and Vehicle Tracking using SURF Method
| Autor: | Hernsoo Hahn, Jae-Hyoung Yu, Youngjoon Han |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Engineering
Vehicle tracking system business.industry Reliability (computer networking) Frame (networking) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Tracking (particle physics) Object (computer science) Image (mathematics) Wavelet Calibration Computer vision Artificial intelligence business |
| Zdroj: | Journal of the Korea Society of Computer and Information. 17:71-80 |
| ISSN: | 1598-849X |
| DOI: | 10.9708/jksci.2012.17.1.071 |
| Popis: | This paper proposes vehicle detection and tracking algorithm using a CCD camera. The proposed algorithm uses Haar-like wavelet edge detector to detect features of vehicle and estimates vehicle`s location using calibration information of an image. After that, extract accumulated vehicle information in continuous k images to improve reliability. Finally, obtained vehicle region becomes a template image to find same object in the next continuous image using SURF(Speeded Up Robust Features). The template image is updated in the every frame. In order to reduce SURF processing time, ROI(Region of Interesting) region is limited on expended area of detected vehicle location in the previous frame image. This algorithm repeats detection and tracking progress until no corresponding points are found. The experimental result shows efficiency of proposed algorithm using images obtained on the road. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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