Abstract
Heterogeneous car video recorders can capture scene information with different modalities including viewing angles, resolutions, and lens sensors. Traditional methods cannot accurately perform image stitching on the images captured by heterogeneous cameras. This paper presents an efficient method to stitch heterogeneous images by allowing a driver to view an ultra-wide angle without blind spots. It extracts bounding boxes of brake lights and license plate numbers as feature points to be matched. A homography matrix is computed to stitch the heterogeneous video images. Experimental results show that our proposed method can stitch images accurately and efficiently, which is superior to the existing methods.
Original language | English (US) |
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Article number | 1755008 |
Journal | International Journal of Pattern Recognition and Artificial Intelligence |
Volume | 31 |
Issue number | 5 |
DOIs | |
State | Published - May 1 2017 |
All Science Journal Classification (ASJC) codes
- Software
- Artificial Intelligence
- Computer Vision and Pattern Recognition
Keywords
- Video stitching
- big view
- car video recorder
- heterogeneous recorder
- ultra-wide-angle road scene