Abstract
Computer Vision, encompassing 3D Vision and 3D scene Reconstruction, is a field of importance to real-world problems involving 3D views of scenes. The goal of the proposed system is to retrieve 3D scenes from the database, and further augment the scenes in an iterative manner based on the user’s commands to finally produce the required output 3D scenes, in the form of a suggestive interface. The process is done recursively to facilitate additions and deletions, until the desired scene is generated. In addition to synthesizing the required 3D indoor scenes from text, a speech recognition system has been integrated with the system that will enable the users to choose from either modes of input. The application includes the projection and rendering of 3D scenes which will enable a 360-\({^\circ }\) view of the scene. The robustness of scene generation and quick retrieval of scenes will promote the usage of this work in avenues such as story telling, interior designing, and as a helpful educational tool for autistic children.
S. Sharadha, K. Shreya, C. Vallikannu—Contributed equally to this paper.
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Srinivasan, S., Kumar, S., Chockalingam, V., S., C. (2021). 3DSRASG: 3D Scene Retrieval and Augmentation Using Semantic Graphs. In: Marreiros, G., Melo, F.S., Lau, N., Lopes Cardoso, H., Reis, L.P. (eds) Progress in Artificial Intelligence. EPIA 2021. Lecture Notes in Computer Science(), vol 12981. Springer, Cham. https://doi.org/10.1007/978-3-030-86230-5_25
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