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RGB-D Segmentation Applications in 3D Reconstruction Problem Based on Depth Map Data

Student: Bobrov Roman

Supervisor: Ilya Makarov

Faculty: Faculty of Computer Science

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 7

Year of Graduation: 2017

RGB-D segmentation often serves as an auxiliary tool in object recognition, detection and tracking, classification, and other relevant problems. Depending on the problem, you may need to distinguish, for example, a flat surface on the image to evaluate room geometry, to determine the location of the “background” in the frame and the to extract one person from the crowd. Finally, in most cases, the use of segmentation reduces the dimensionality of the data to supply input to other algorithms. This paper discusses the algorithms of image segmentation and applies some heuristics to improve the quality of the resulting image partitions. Comparative analysis of algorithms in terms of segmentation quality and speed is given.

Full text (added May 28, 2017)

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