An Efficient Image Stitching Method for Heterogeneous Car Videos Based on Bounding Boxes of Features
Document Type
Article
Publication Date
5-1-2017
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.
Identifier
85007200139 (Scopus)
Publication Title
International Journal of Pattern Recognition and Artificial Intelligence
External Full Text Location
https://doi.org/10.1142/S0218001417550084
ISSN
02180014
Issue
5
Volume
31
Recommended Citation
Tsai, Chun Ming and Shih, Frank Y., "An Efficient Image Stitching Method for Heterogeneous Car Videos Based on Bounding Boxes of Features" (2017). Faculty Publications. 9607.
https://digitalcommons.njit.edu/fac_pubs/9607
