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VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world.This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR.At the advent of V ...
Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...
This paper addresses the problem of compression of 3D point cloud sequences that are characterized by moving 3D positions and color attributes. As temporally successive point cloud frames are similar, motion estimation is key to effective compression of th ...
Institute of Electrical and Electronics Engineers2016
The growth of motion capture systems has contributed to the proliferation of human motion database, mainly because human motion is important in many applications, ranging from games entertainment and films to sports and medicine. However, the various captu ...
This paper presents a novel algorithm for computing the relative motion between images from compressed linear measurements. We propose a geometry based correlation model that describes the relative motion between images by translational motion of visual f ...
This paper aims to maximize the profitability of a set of brand SKUs stocked at a particular retailer by optimizing the number of facings for each product. Based on the past data, a set of variables such as retail price of different SKUs, linear footage th ...
Motion LoD (Level of Detail) is a preprocessing technique that generates multiple details of captured motion by eliminating joints. This LoD technique is applied to movie, game or VR environments for the purpose of improving speed of crowd animation. So fa ...
In this paper we present a new methodology to extract the small error-prone motion recorded during a Computed Tomography (CT) imaging directly from the sinogram. In comparison to the use of the usual reconstructed images, this approach has the advantage to ...
We present a probabilistic approach to learn robust models of human motion through imitation. The association of Hidden Markov Model (HMM), Gaussian Mixture Regression (GMR) and dynamical systems allows us to extract redundancies across multiple demonstrat ...
Motion estimation (ME) methods based on differential techniques provide useful information for video analysis, and moreover it is relatively easy to embed into them regularity constraints en- forcing for example, contour preservation. On the other hand, th ...
