Object recognition and segmentation by non-rigid quasi-dense matching

In this paper, we present a non-rigid quasi-dense matching method and its application to object recognition and segmentation. The matching method is based on the match propagation algorithm which is here extended by using local image gradients for adapting the propagation to smooth non-rigid deformations of the imaged surfaces. The adaptation is based entirely on the local properties of the images and the method can be hence used in non-rigid image registration where global geometric constraints are not available. Our approach for object recognition and segmentation is directly built on the quasi-dense matching. The quasi-dense pixel matches between the model and test images are grouped into geometrically consistent groups using a method which utilizes the local affine transformation estimates obtained during the propagation. The number and quality of geometrically consistent matches is used as a recognition criterion and the location of the matching pixels directly provides the segme...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Esa Rahtu, Janne Heikkilä, Juho Kannala, Sami S. Brandt
• Keywords: Computer Vision, CVPR 2008, Matching Method, Non-rigid Deformations, Non-rigid Image Registration, Non-rigid Quasi-dense Matching, Notable Geometric Deformations