3D Reconstruction based on binocular data is significant to machine vision,and has the following basic steps: camera-self calibration,stereo matching,depth extraction,and 3D representation.Due to the high precision requirement,the configuration of dual camera in the binocular reconstruction system is often too strict to implement.And stereo matching as the main task can hardly be done well in both time computing and precision.Our study proposes a new and high efficiency processing flow,in which we use a consumer camera.The kernel feature is proposed in calibration stage to rectify the epipolar.The most prominent breakthrough is that we segment the objects in the camera into background and foreground,for which system obtains the disparity by different method: local window matching and kernel feature-based matching.Extensive experiments demonstrate our proposed algorithm represents accurate 3D model.