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Segmentation de maillages 3D par l'exemple

Abstract : In this dissertation, we present a new method to segment 3D models into their functional parts. The segmentation is performed by a transfer approach: a semantic-oriented segmentation of an object is calculated using a pre-segmented example model from the same class (chairs, humans, etc.). To this end, we adapted and extended the random walk segmentation method which allowed us to transform our problem into a problem of locating and matching seed faces. Our method consists of four fundamental steps: establishing correspondences between the example and the target model, localizing seeds to initialize regions in the target model, computing the segments and refining their boundaries in the target model. We decomposed our approach in two, taking into account similarity criteria which differ regarding the object type (rigid vs. articulated). The first approach is dedicated to rigid objects (chairs, airplanes, etc.), where the matching is based on rigid transformations to determine the best alignment between the functional parts of the compared objects. The second one focused on articulated objects (humans, quadrupeds, etc.), where coarse topological shape attributes are used in a skeleton-based approach to cover larger pose variations when computing correspondences between functional parts. We show through qualitative and quantitative evaluations that our method improves upon individual segmentation techniques and obtains results that are close to the co-segmentation techniques results with an important calculation time reduction.
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https://hal.inria.fr/tel-01093509
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  • HAL Id : tel-01093509, version 2

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Esma Elghoul. Segmentation de maillages 3D par l'exemple. Synthèse d'image et réalité virtuelle [cs.GR]. Télécom ParisTech, 2014. Français. ⟨NNT : 2014ENST0051⟩. ⟨tel-01093509v2⟩

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