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.