HOLISTIC SHAPE-BASED OBJECT RECOGNITION USING BOTTOM-UP IMAGE STRUCTURES Praveen Srinivasan Jianbo Shi, Associate Professor of Computer and Information Science Object recognition performance that rivals human ability is one of the primary goals of computer vision research. While recognition may take many forms, key tasks include detection, estimating object pose, and segmenting the object from ...

This paper introduces an anisotropic Laplace-Beltrami operator for shape analysis. While keeping useful properties of the standard Laplace-Beltrami operator, it introduces variability in the directions of principal curvature, giving rise to a more intuitive and semantically meaningful diffusion process. Although the benefits of anisotropic diffusion have already been noted in the area of mesh p...

This paper presents a method of hand posture estimation from silhouette images taken by multiple cameras. For each image, we extract a feature vector from the silhouette contour of the hand. We construct an eigenspace by the feature vectors extracted from the hands of various postures. The feature vectors projected into the eigenspace are registered as models. The matching criterion of each ima...

In this technical report we derive the analytic form of the Hessian matrix for shape matching energy. Shape matching (Fig. 1) is a useful technique for meshless deformation, which can be easily combined with multiple techniques in real-time dynamics (refer to [MHTG05, BMM15] for more details). Nevertheless, it has been rarely applied in scenarios where implicit (such as backward differentiation...

Computer vision has been an active research area for the past few decades. It is being used in many fields of industries for example digit recognition and handwriting recognition in banks, industrial parts recognition etc. Shape matching is an important sub-domain of Computer Vision, and relies on effective shape representation techniques. These techniques must be developed in order to effectiv...

Minutiae-based methods have been used in many commercial fingerprint matching systems. Based primarily on a point pattern matching model, these methods rely heavily on the accuracy of minutiae extraction and the detection of landmarks like core and delta for pre-alignment. Spurious and missing minutiae can both introduce errors in minutiae correspondence. Equally problematic is the inability to...