Semantic Object Selection and Detection for Diminished Reality Based on SLAM with Viewpoint Class

Yoshikatsu Nakajima; Shohei Mori; Hideo Saito

doi:10.1109/ISMAR-Adjunct.2017.98

Semantic Object Selection and Detection for Diminished Reality Based on SLAM with Viewpoint Class

Yoshikatsu Nakajima, Shohei Mori, Hideo Saito

Department of Information and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

We propose a novel diminished reality method which is able to (i) automatically recognize the region to be diminished, (ii) work with a single RGB-D sensor, and (iii) work without pre-processing to generate a 3D model of the target scene by utilizing SLAM, segmentation, and recognition framework. Especially, regarding the recognition of the area to be diminished, our method is able to maintain high accuracy no matter how the camera moves by distributing the viewpoints for each object uniformly and aggregating recognition results from each distributed viewpoint as the same weight. These advantages are demonstrated on the UW RGB-D Dataset and Scenes.

Original language	English
Title of host publication	Adjunct Proceedings of the 2017 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	338-343
Number of pages	6
ISBN (Electronic)	9780769563275
DOIs	https://doi.org/10.1109/ISMAR-Adjunct.2017.98
Publication status	Published - 2017 Oct 27
Event	16th Adjunct IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017 - Nantes, France Duration: 2017 Oct 9 → 2017 Oct 13

Other

Other	16th Adjunct IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017
Country	France
City	Nantes
Period	17/10/9 → 17/10/13

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Keywords

Convolutional Neural Network
Diminished Reality
Object Recognition
Segmentation
SLAM

ASJC Scopus subject areas

Human-Computer Interaction
Media Technology
Computer Science Applications

Cite this

Nakajima, Y., Mori, S., & Saito, H. (2017). Semantic Object Selection and Detection for Diminished Reality Based on SLAM with Viewpoint Class. In Adjunct Proceedings of the 2017 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017 (pp. 338-343). [8088517] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISMAR-Adjunct.2017.98

Semantic Object Selection and Detection for Diminished Reality Based on SLAM with Viewpoint Class. / Nakajima, Yoshikatsu; Mori, Shohei; Saito, Hideo.

Adjunct Proceedings of the 2017 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 338-343 8088517.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nakajima, Y, Mori, S & Saito, H 2017, Semantic Object Selection and Detection for Diminished Reality Based on SLAM with Viewpoint Class. in Adjunct Proceedings of the 2017 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017., 8088517, Institute of Electrical and Electronics Engineers Inc., pp. 338-343, 16th Adjunct IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017, Nantes, France, 17/10/9. https://doi.org/10.1109/ISMAR-Adjunct.2017.98

Nakajima Y, Mori S, Saito H. Semantic Object Selection and Detection for Diminished Reality Based on SLAM with Viewpoint Class. In Adjunct Proceedings of the 2017 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 338-343. 8088517 https://doi.org/10.1109/ISMAR-Adjunct.2017.98

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Access to Document

10.1109/ISMAR-Adjunct.2017.98