Version 1
: Received: 2 May 2017 / Approved: 3 May 2017 / Online: 3 May 2017 (09:19:59 CEST)
How to cite:
He, L.; Yang, J.; Kong, B.; Wang, C. An Automatic Measurement Method for Absolute Depth of Objects in Two Monocular Images Based on SIFT Feature. Preprints2017, 2017050028. https://doi.org/10.20944/preprints201705.0028.v1
He, L.; Yang, J.; Kong, B.; Wang, C. An Automatic Measurement Method for Absolute Depth of Objects in Two Monocular Images Based on SIFT Feature. Preprints 2017, 2017050028. https://doi.org/10.20944/preprints201705.0028.v1
He, L.; Yang, J.; Kong, B.; Wang, C. An Automatic Measurement Method for Absolute Depth of Objects in Two Monocular Images Based on SIFT Feature. Preprints2017, 2017050028. https://doi.org/10.20944/preprints201705.0028.v1
APA Style
He, L., Yang, J., Kong, B., & Wang, C. (2017). An Automatic Measurement Method for Absolute Depth of Objects in Two Monocular Images Based on SIFT Feature. Preprints. https://doi.org/10.20944/preprints201705.0028.v1
Chicago/Turabian Style
He, L., Bin Kong and Can Wang. 2017 "An Automatic Measurement Method for Absolute Depth of Objects in Two Monocular Images Based on SIFT Feature" Preprints. https://doi.org/10.20944/preprints201705.0028.v1
Abstract
It is one of very important and basic problem in compute vision field that recovering depth information of objects from two-dimensional images. In view of the shortcomings of existing methods of depth estimation, a novel approach based on SIFT (the Scale Invariant Feature Transform) is presented in this paper. The approach can estimate the depths of objects in two images which are captured by an un-calibrated ordinary monocular camera. In this approach, above all, the first image is captured. All of the camera parameters remain unchanged, and the second image is acquired after moving the camera a distance d along the optical axis. Then image segmentation and SIFT feature extraction are implemented on the two images separately, and objects in the images are matched. Lastly, an object depth can be computed by the lengths of a pair of straight line segments. In order to ensure that the best appropriate a pair of straight line segments are chose and reduce the computation, the theory of convex hull and the knowledge of triangle similarity are employed. The experimental results show our approach is effective and practical.
Computer Science and Mathematics, Computer Vision and Graphics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
