A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented. The focus is on a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition. Each

Abstract—The advent of RGB-D cameras which provide synchronized range and video data creates new opportunities for exploiting both sensing modalities for various robotic applications. This paper exploits the strengths of vision and range measurements and develops a novel robust algorithm

This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align

and motion estimation has allowed development of vision based localization techniques. De-spite much progress, there are disadvantages to both range sensing and vision techniques making localization and mapping that is inexpensive and robust hard to at-tain. With the advent of RGB-D cameras which provide

The purpose of this chapter is to present a survey of recent publications concerning medical image registration techniques. These publications will be classified according to a model based on nine salient criteria, the main dichotomy of which is extrinsic versus intrinsic methods The statistics

Abstract — We present an approach to simultaneous local-ization and mapping (SLAM) for RGB-D cameras like the Microsoft Kinect. Our system concurrently estimates the tra-jectory of a hand-held Kinect and generates a dense 3D model of the environment. We present the key features of our approach

We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian

A heuristic method has been developed for registering two sets of 3-D curves obtained by using an edge-based stereo system, or two dense 3-D maps obtained by using a correlation-based stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately

This paper presents the design and evaluation of Pastry, a scalable, distributed object location and routing scheme for wide-area peer-to-peer applications. Pastry provides application-level routing and object location in a potentially very large overlay network of nodes connected via the Internet

Stable local feature detection and representation is a fundamental component of many image registration and object recognition algorithms. Mikolajczyk and Schmid [14] recently evaluated a variety of approaches and identified the SIFT [11] algorithm as being the most resistant to common image