An efficient pixel-based technique for visual verification of 3-D object hypotheses

The technique proceeds in three steps: firstly, the visible-edge image of the hypothesized model object is constructed; secondly, this image is superimposed on the scene edge image; finally, corresponding pixels in the two images are compared to gather votes for the validity of the hypothesis. Uncertainty in estimating the locations of both scene and model edge pixels is handled by dilating the scene edge image. An analytical method is presented for determining the extent of dilation, assuming some error bound on the object pose. The proposed technique has several important advantages over the common feature-based techniques. Firstly, it is much simpler to implement. Secondly, the time complexity of verifying a hypothesis is made independent of the scene complexity (number and types of scene features). Thirdly, it is insensitive to imperfections of the feature extraction process. Finally the technique is easy to implement on the existing parallel vision/graphics hardware; thus it is suitable for real-time applications