Object Recognition from Local Scale-Invariant Features

Proc. of the International Conference on Computer Vision, Corfu (Sept. 1999) An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation,and rotation, and partially invariant to illuminationchanges and affine or 3D projection. These features share similar properties with neurons in inferior temporal cortex that are used for object recognition in primate vision. Features are efficiently detected through a staged filtering approach that identifies stable points in scale space. Image keys are created that allow for local geometric deformations by representing blurred image gradients in multiple orientation planes and at multiple scales. The keys are used as input to a nearest-neighbor indexing method that identifies candidate object matches. Final verification of each match is achieved by finding a low-residual least-squares solution for the unknown model parameters. Experimental results show that...

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: David G. Lowe
• Keywords: Candidate Object, Computer Vision, ICCV 1999, Inferior Temporal Cortex, Local Geometric Deformations, Local Image Features, Robust Object Recognition