We propose a framework for compressive sensing of images with local geometric features. Specifically, let x ∈ R be an N -pixel image, where each pixel p has value xp. The image is acquired by computing the measurement vector Ax, where A is an m×N measurement matrix for some m N . The goal is then to design the matrix A and recovery algorithm which, given Ax, returns an approximation to x. In th...

ABSTRAC: -This research aims at the extraction of geometric features from Urdu ligatures. Though structural features are robust, its extraction and analysis is exceptionally complex and time-consuming task. The extraction and analysis is uncomplicated in case of the geometric features. Geometric features are language, script and font independent. There are twelve significant geometric features ...

he Artificial Visual System (AVS) (Figure 1) ~mputational framework for computer vision. [1] n AVS convolves an image with a series of D mtial filters, yielding a series of D filtered aages. While any set of filters can be applied in ds way, families of filters can be designed to .~oduce a compact, task-specific decomposition or a meral, task-independent decomposition of the aage. The filter se...

The visual richness of computer graphics applications is frequently limited by the difficulty of obtaining high-quality, detailed 3D models. This paper proposes a method for realistically transferring details (specifically, displacement maps) from existing high-quality 3D models to simple shapes that may be created with easy-to-learn modeling tools. Our key insight is to use metric learning to ...

As robots begin to collaborate with humans in everyday workspaces, they will need to understand the functions of tools and their parts. To cut an apple or hammer a nail, robots need to not just know the tool’s name, but they must localize the tool’s parts and identify their functions. In this extended abstract, we give an overview of our work on localizing and identifying object part affordance...