7,097 research outputs found

    Self-correction of 3D reconstruction from multi-view stereo images

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    We present a self-correction approach to improving the 3D reconstruction of a multi-view 3D photogrammetry system. The self-correction approach has been able to repair the reconstructed 3D surface damaged by depth discontinuities. Due to self-occlusion, multi-view range images have to be acquired and integrated into a watertight nonredundant mesh model in order to cover the extended surface of an imaged object. The integrated surface often suffers from “dent” artifacts produced by depth discontinuities in the multi-view range images. In this paper we propose a novel approach to correcting the 3D integrated surface such that the dent artifacts can be repaired automatically. We show examples of 3D reconstruction to demonstrate the improvement that can be achieved by the self-correction approach. This self-correction approach can be extended to integrate range images obtained from alternative range capture devices

    Simulation and Visualization of Medical Application to the Inner Ear of the Guinea Pig to Reduce Animal Experiments

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    We present a novel approach to simulate drug application to the inner ear of the guinea pig with the goal to reduce animal experiments and to increase the accuracy of measurements. The framework is based on a tetrahedral grid representing the individual compartments of the cochlea, associated with a finite element model used to simulate medical diffusion and clearance. In a first simulation scenario, we were able to compute transfer coefficients between the inner compartments of the ear, validating experiments from the literature, and to prove the existence of clearance at the inner scala tympani. In a second scenario, the cochlea was unwound to obtain a one-dimensional model for efficient simulation-based transfer coefficient identification. These coefficients are useful to predict the impact of novel medication application systems

    Crepuscular Rays for Tumor Accessibility Planning

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    On-barn pig weight estimation based on body measurements by structure-from-motion (SfM)

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    Information on the body shape of pigs is a key indicator to monitor their performance and health and to control or predict their market weight. Manual measurements are among the most common ways to obtain an indication of animal growth. However, this approach is laborious and difficult, and it may be stressful for both the pigs and the stockman. The present paper proposes the implementation of a Structure from Motion (SfM) photogrammetry approach as a new tool for on-barn animal reconstruction applications. This is possible also to new software tools allowing automatic estimation of camera parameters during the reconstruction process even without a preliminary calibration phase. An analysis on pig body 3D SfM characterization is here proposed, carried out under different conditions in terms of number of camera poses and animal movements. The work takes advantage of the total reconstructed surface as reference index to quantify the quality of the achieved 3D reconstruction, showing how as much as 80% of the total animal area can be characterized
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