In order to match video sequence images efficiently and considering the effectiveness and efficiency of the SVD matching algorithm

this paper describes a more advanced SVD multi view video image matching algorithm based on a new type of invariant feature and outlier rejection strategy. The features are located at Harris corners and oriented using a blurred local gradient. This defines a rotationally invariant frame which is sampled as a feature descriptor. The color information is introduced into the distance function of SVD matching algorithm. The outliers are rejected based on motion consistency. For motion consistency a motion model was fit first between the matched points

and the threshold was set adaptively using the deviations of the motion to reject the outliers. This algorithm uses oriented patch to adapt to the effect of rotation

color features to remove the uncertainty

and motion consistency to increase the correct match ratio. The experimental results show that the algorithm can obtain lots of matching points between wide base line images

even if there is rotational transformation and different lighting conditions between two images

which proof that the algorithm has practical value.