JOURNAL ARTICLE

Motion recovery using the image interpolation algorithm and an RGB-D camera

Abstract

In this paper, a simple and robust method to recover ego-motion from a RGB-D camera is proposed. For our algorithm, no assumptions about the moving object or dynamic scenes are needed. Using the optical flow fields computed from the image sequence and depth information obtained from the RGB-D camera we estimate the ego-motion parameters. Our experiments have shown that using the intensity image and corresponding depth value can be very helpful for ego-motion estimation. We also show the experimental results of different scenarios, such as translation only and combination of translation and rotation.

Keywords:
Computer vision Artificial intelligence Optical flow RGB color model Motion field Rotation (mathematics) Translation (biology) Interpolation (computer graphics) Computer science Motion interpolation Motion estimation Motion (physics) Algorithm Image (mathematics) Object (grammar) Block-matching algorithm Video tracking

Metrics

2
Cited By
0.48
FWCI (Field Weighted Citation Impact)
20
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Optical measurement and interference techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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