RGB-Dカメラによる環境の3次元計測に基づく実時間隠消現実感(<特集>複合現実感6)

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  • Real-Time Diminished Reality Based on 3D Measurement of Environment Using an RGB-D Camera(<Special Issue>Mixed Reality)
  • RGB-Dカメラによる環境の3次元計測に基づく実時間隠消現実感
  • RGB-Dカメラ ニ ヨル カンキョウ ノ 3ジゲン ケイソク ニ モトズク ジツジカンインショウゲン ジッカン

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In this paper, we present a system for Diminished Reality (DR). In this system, we have two ways to perform DR: one is for a static target scene, and the other is a dynamic target scene. In the case of a static target scene, we create 3D environment model beforehand. Viewpoint Generative Learning is performed based on this model, and a database of feature descriptors is constructed. When DR is performed, feature descriptors of a smartphone image are compared with those of the database, then matched and a relative position between the smartphone and the model is computed. The model which corresponds to the position that the user touches on the smartphone is hidden and the model behind the position is drawn on the smartphone image. In the case of a dynamic target scene, feature values of a smartphone image and an RGB-D camera image are extracted for every frame, then matched and a relative position between the smartphone and the RGB-D camera is computed. Point cloud data is used instead of a model. The area specified by the user is hidden and the point cloud data is drawn on the smartphone image. We can perform real-time processing because we send the smartphone image to the PC which returns obstacle-removed images for every frame. Our experiment revealed it was possible to perform DR on the smartphone in approximately 8fps when the target scene had 3D shapes.

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