视觉里程计
光流
人工智能
计算机视觉
计算机科学
像素
里程计
机器人学
光场
特征(语言学)
流量(数学)
领域(数学)
跟踪(教育)
噪音(视频)
机器人
图像(数学)
数学
移动机器人
纯数学
语言学
教育学
哲学
几何学
心理学
作者
Donald G. Dansereau,Ian Mahon,Oscar Pizarro,Stefan B. Williams
标识
DOI:10.1109/iros.2011.6095080
摘要
Three closed-form solutions are proposed for six degree of freedom (6-DOF) visual odometry for light field cameras. The first approach breaks the problem into geometrically driven sub-problems with solutions adaptable to specific applications, while the second generalizes methods from optical flow to yield a more direct approach. The third solution integrates elements into a remarkably simple equation of plenoptic flow which is directly solved to estimate the camera's motion. The proposed methods avoid feature extraction, operating instead on all measured pixels, and are therefore robust to noise. The solutions are closed-form, computationally efficient, and operate in constant time regardless of scene complexity, making them suitable for real-time robotics applications. Results are shown for a simulated underwater survey scenario, and real-world results demonstrate good performance for a three-camera array, outperforming a state-of-the-art stereo feature-tracking approach.
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