Optical Flow Detection Using a General Noise Model

スポンサーリンク

概要

• 論文の詳細を見る

• In the usual optical flow detection, the gradient constraint, which expresses the relationship between the gradient of the image intensity and its motion, is combined with the least-squares criterion. This criterion means assuming that only the time derivative of the image intensity contains noise. In this paper, we assume that all image derivatives contain noise and derive a new optical flow detection technique. Since this method requires the knowledge about the covariance matrix of the noise, we also discuss a method for its estimation. Our experiments show that the proposed method can compute optical flow more accurately than the conventional method.

• 一般社団法人電子情報通信学会の論文
• 1996-07-25

著者

• Ohta Naoya

  Department Of Computer Science Gunma University

関連論文

• Optimal Structure-from-Motion Algorithm for Optical Flow
• Optical Flow Detection Using a General Noise Model
• Uncertainty Models of the Gradient Constraint for Optical Flow Computation
• Optimal Robot Self-Localization and Accuracy Bounds

スポンサーリンク