6 March 2012 3-D reconstruction using image sequences based on projective depth and simplified iterative closest point
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Abstract
The authors propose a new algorithm for 3-D construction from a sequence of images based on a new corollary that the projective depth can be comprehended as a scalar factor between two 3-D points when reconstructed from three images. This algorithm constructs the partial models of an object using two consecutive images in the image sequence and integrates the obtained partial models to a complete one on the basis of this new corollary. In order to avoid accumulation of errors in the integration process, this algorithm modifies the reconstruction results based on a simplified Iterative Closest Point (ICP) algorithm. We have carried out two groups of experiments based on images captured from a library environment. In one group of experiments, sparse points are used to reconstruct regular objects; in the other group of experiments, dense points are employed. We compared experimental results of the proposed algorithm with the optimization method using the fundamental matrix, which demonstrated that the proposed algorithm yielded better efficiency and accuracy of the 3-D reconstruction. Experiments also showed that the reconstruction errors of the proposed method were within 5%.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Keju Peng, Keju Peng, Xin Chen, Xin Chen, Dongxiang Zhou, Dongxiang Zhou, Yongping Zhai, Yongping Zhai, Yunhui Liu, Yunhui Liu, } "3-D reconstruction using image sequences based on projective depth and simplified iterative closest point," Optical Engineering 51(2), 021110 (6 March 2012). https://doi.org/10.1117/1.OE.51.2.021110 . Submission:
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