Dynamic Extended Rectangle Based Method for 3D Visual Scene Segmentation

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A novel approach for semantic scene segmentation with computer vision is presented in this paper. The principle goal is to capture the scene distribution of the different zones of any multipurpose hall, taking into account both monocular visual cues (texture feature) and depth information. A feature extraction strategy based on a dynamic extension of the rectangular patches is proposed in order to provide a more accurate segmentation and to avoid redundancy penalties.The depth constraints control the initial classification decision that is obtained by a neuro-fuzzy classifier. An experimental study is applied on our dataset to demonstrate this approach on his different optimization stages.
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Scene Segmentation; Texture; Depth Information; Neuro-Fuzzy Classification; Pattern Recognition

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