Edge and Intensity based Visual Odometry for RGB-D Camera
| Autor: | Guoliang Zhang, Hui Xu, Erliang Yao, Hexin Zhang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
business.industry Detector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Tracking (particle physics) Nonlinear programming Computer Science::Computer Vision and Pattern Recognition RGB color model Computer vision Artificial intelligence Enhanced Data Rates for GSM Evolution Visual odometry business Distance transform Pose |
| Zdroj: | 2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC). |
| Popis: | We propose a novel visual odometry based on edge and intensity for RGB-D cameras. The proposed method is based on frame-to-keyframe tracking, which aligns the edges extracted by the Canny detector and minimizes photometric errors to estimate the camera motion. Edge alignment is realized by minimization of distance transform (DT) errors which are calculated by the edges. The huber robust cost function and the Student-t distribution are applied to weight the DT errors and the photometric errors respectively. A joint optimization for DT errors and photometric errors is generated for pose estimation by nonlinear optimization. The method is evaluated with the TUM RGB-D dataset. Our method can run in real time on a laptop computer. |
| Databáze: | OpenAIRE |
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