Title: A combination of 'feature mapping' and 'block' approaches to reduce the matching area of stereoscopic algorithms

Authors: Djaber Rouabhia; Nour Eddine Djedi

Addresses: Mohamed Khider University, 7000, Biskra, Algeria ' Mohamed Khider University, 7000, Biskra, Algeria

Abstract: In this paper, we propose a new approach to restrict the matching field of stereoscopic algorithms. It has been found that computing the disparity map implies using the whole image for a wide range of stereoscopic methods, thus, leading to extra-time calculation and visual artefacts in the results. Based on this observation, we derived an approach that significantly reduces the evaluated time of stereoscopic algorithms and avoids noises appearing in the result. The proposed approach introduces a strong association between silhouette edges and stereoscopic algorithms by using only the geometric information present in the images to restrict the matching area. The proposed method aims to limit the matching zone to the exact geometry of the analysed object, avoiding, therefore, extra times and undesirable noises. We did not use hard-coding algorithms or expensive equipment, and we got accepted results in terms of time and accuracy.

Keywords: 3D reconstruction; stereo-vision; multi-view stereo; MVS; disparity map; feature mapping; block.

DOI: 10.1504/IJCVR.2023.134310

International Journal of Computational Vision and Robotics, 2023 Vol.13 No.6, pp.641 - 657

Received: 30 Nov 2021
Accepted: 02 Jun 2022
Published online: 18 Oct 2023 *

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