Abstract
In this paper, the problem of estimating the depth of an object from its monocular image is addressed. Here, basically, an algorithm is developed, which performs shape matching, and as a result, achieve accurate depth maps of objects. In the algorithm, first, an optimal camera position is determined. Then, the 3D model is projected onto the image plane of the camera, yielding a projected 2D image of the 3D model. An objective function determines a score based on graph-based feature matching, and the depth map is extracted from the geometrical information of the 3D model. Finally, the depth map and the original image are combined to create a 3D point cloud simulation of the object. Experimental analysis shows the efficacy of the proposed method.
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Das, B., Dutta, H.P.J., Bhuyan, M.K. (2021). Graph-Based Depth Estimation in a Monocular Image Using Constrained 3D Wireframe Models. In: Singh, S.K., Roy, P., Raman, B., Nagabhushan, P. (eds) Computer Vision and Image Processing. CVIP 2020. Communications in Computer and Information Science, vol 1378. Springer, Singapore. https://doi.org/10.1007/978-981-16-1103-2_35
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