Verifying and combining different visual cues into a 3-D model

The authors attempt to combine results from different vision cues such as contour, motion and shading in an image sequence to obtain as complete a 3-D model as possible. Two problems must be solved. First, different features may appear to be the same image data. They should be classified so that different methods can be applied precisely. Second, output from different approaches may supplement, or overlap, each other. They should be qualified and then combined correctly and effectively. These issues are addressed by analyzing an image sequence taken when objects rotate around an axis. The features are verified according to their behaviour in the continuous images. Unknown areas and areas with single or multiple measurements are located. A strategy for combining these data is given