Detection and segmentation of moving objects from dynamic RGB and depth images

Naotomo Tatematsu; Jun Ohya; Larry Davis

doi:10.1007/978-3-662-48247-6_2

Detection and segmentation of moving objects from dynamic RGB and depth images

Naotomo Tatematsu, Jun Ohya, Larry Davis

Research output: Contribution to journal › Article

1 Citation (Scopus)

Abstract

This paper proposes a method that combines Temporal Modified-RANSAC(TMR) with a fixation-based segmentation algorithm for reconstructing the 3D structure of moving and still objects that are tracked in video and depth image sequences acquired by moving Kinect

Original language	English
Pages (from-to)	19-34
Number of pages	16
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8971
DOIs	https://doi.org/10.1007/978-3-662-48247-6_2
Publication status	Published - 2015

Keywords

Fixation-based segmentation
Kinect
Reconstruction
Segmentation
Temporal modified RANSAC

ASJC Scopus subject areas

Computer Science(all)
Theoretical Computer Science

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Tatematsu, N., Ohya, J., & Davis, L. (2015). Detection and segmentation of moving objects from dynamic RGB and depth images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8971, 19-34. https://doi.org/10.1007/978-3-662-48247-6_2

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