Ego-Motion Asynchronous Estimation Based on Fish-Eye Camera
YU Hong-fe · Dianzi xuebao · 2013
Ego-motion parameter estimation is one of the key problems in driver assistance and robot navigation, etc.An asynchronous estimation method which is applicable to fish-eye camera is proposed.The method estimates rotation parameters and translation parameters respectively based on feature classification and virtual plane projection.It solves the problem in the previous algorithms that rotation parameters and translation parameters influence each other when estimating at the same time, and improves the estimation accuracy.Firstly, camera motion model is simplified with platform motion characteristics, and background features from different distances and positions are classified according to their roles in motion estimation.The motion laws of features in each class are analyzed and induced.And then according to the laws, the distant background features and general background features are used to estimate the rotation parameters, and ground features are used to estimate the translation parameters.The experimental results show that the proposed method is less influenced by illumination or outliers, and more accurate and robust than some traditional methods.