Abstract
We have developed an efficient algorithm to compute an Euclidean reconstruction from only two wide-baseline color images captured with a hand-held digital camera. The classical reconstruction scheme has been improved to boost the number of matches by a hierarchical epipolar constraint during an iterative process and an ultimate step of dense matching based on affine transformation. At the output, between three to four thousands points are reconstructed in 2 minutes on 1024x768 images. The stability of the algorithm has been evaluated by some repetitive tests and the quality of the reconstruction is assessed according to a metric ground truth provided by an industrial 3D scanner. The averaged error on 3D points is around 3.5% reported to the model depth. Such a precision makes this technique suitable for wound volumetric assessment in clinical environments using a hand held digital camera.
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