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Motion detection is a hard task for intelligent vehicles since target motion is mixed with ego-motion caused by moving cameras. This paper proposes a stereo-motion fusion method for detection of moving objects from a moving platform. A 3-dimensional motion model integrating stereo and optical flow has been established to estimate the ego-motion flow. The mixed flow is calculated from an edge-indexed correspondence matching algorithm. The difference between the mixed flow and the ego-motion flow yields residual target motion flow where the intact target is segmented from. To estimate the ego-motion flow, a visual odometer has been implemented. We first extract some feature points in the ground plane that are identified as static points using the height constraint and Harris algorithm. And then, 6 DOF motion parameters of the moving camera are calculated by fitting the feature points into the linear least square algorithm. The approach presented here is tested on substantial traffic videos, and the results prove the efficiency of the method.

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