Abstract: Different poses of 3D models are very often given in different positions and orientations in space. Since most of the computer graphics algorithms do not satisfy geometric invariance, it is very important to bring shapes into a canonical coordinate frame before any processing. In this paper we consider the problem of finding the best alignment between two or more different poses of the same object represented by triangle meshes sharing the same connectivity. Firstly, we developed a method to select a region of interest (ROI) which has a perfect alignment over the two poses (up to a rigid movement). Secondary, we solved a simplified version of the Largest Common Point-set (LCP) problem with a-priori knowledge about point correspondence, in order to align the ROIs. We eventually align the poses performing least square rigid registration. Our method makes no assumption about the starting positions of the objects and can also be used with more than two poses at once. It is fast, non-iterative, easy to reproduce and brings the poses into the best alignment whatever the initial positions are.
Authors: M. Livesu, R. Scateni.
Rigid registration of different poses of animated shapes.
Journal of WSCG, 21(1):1-10 (WSCG 2013, Plzen, Rep. Ceca).
University of West Bohemia, Giugno 2013.
Abstract: The number and quality of smartphones on the market has dramatically raised lately. Researchers and developers are, thus, more and more pushed to bring algorithms and techniques from desktop environments to mobile platforms. One of the biggest constraints in mobile applications is the fine control of computing power and the relative power consumption. Although smartphones’ manufactures are offering better computing performance and longer battery life, the mobile architecture is not always powerful enough. Furthermore, nowadays, the touchless interaction (e.g., the usage of voice commands) on mobile devices is particularly attractive. The device can also possibly answer to our questions (e.g., Siri-Speech Interpretation and Recognition Interface, which according to Apple is “the intelligent personal assistant that helps you get things done just by asking”). The use of talking avatars can improve the quality of the interaction and make it more useful and pleasant. Since avatars are static models, but the interaction requires dynamics, it is almost obliged to introduce avatars’ animations.
Abstract: Shape reconstruction from raw point sets is a hot research topic. Point sets are increasingly available as primary input source, since low-cost acquisition methods are largely accessible nowadays, and these sets are more noisy than used to be. Standard reconstruction methods rely on normals or signed distance functions, and thus many methods aim at estimating these features. Human vision can however easily discern between the inside and the outside of a dense cloud even without the support of fancy measures. We propose, here, a perceptual method for estimating an indicator function for the shape, inspired from image-based methods. The resulting function nicely approximates the shape, is robust to noise, and can be used for direct isosurface extraction or as an input for other accurate reconstruction methods.
Abstract: Natural User Interfaces are often described as familiar, evocative and intuitive, predictable, based on common skills. Though unquestionable in principle, such definitions don’t provide the designer with effective means to design a natural interface or evaluate a design choice vs another. Two main issues in particular are open: (i) how do we evaluate a natural interface, is there a way to measure ‘naturalness’; (ii) do natural user interfaces provide a concrete advantage in terms of efficiency, with respect to more traditional interface paradigms? In this paper we discuss and compare observations of user behavior in the task of pair programming, performed at a traditional desktop versus a multi-touch table. We show how the adoption of a multi-touch user interface fosters a significant, observable and measurable, increase of nonverbal communication in general and of gestures in particular, that in turn appears related to the overall performance of the users in the task of algorithm understanding and debugging.
Abstract: Recent advances in gesture recognition made the problem of controlling a humanoid robot in the most natural possible way an interesting challenge. Learning from Demonstration field takes strong advantage from this kind of interaction since users who have no robotics knowledge are allowed to teach new tasks to robots easier than ever before. In this work we present a cheap and easy way to implement humanoid robot along with a visual interaction interface allowing users to control it. The visual system is based on the Microsoft Kinect’s RGB-D camera. Users can deal with the robot just by standing in front of the depth camera and mimicking a particular task they want to be performed by the robot. Our framework is cheap, easy to reproduce, and does not strictly depend on the particular underlying sensor or gesture recognition system.