A Generic Framework for Tracking Using Particle Filter With Dynamic Shape Prior

©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TIP.2007.894244Tracking deforming objects involves estimating the global motion of the object and its local deformations as functions of time. Tracking algorithms using Kalman filters or particle filters (PFs) have been proposed for tracking such objects, but these have limitations due to the lack of dynamic shape information. In this paper, we propose a novel method based on employing a locally linear embedding in order to incorporate dynamic shape information into the particle filtering framework for tracking highly deformable objects in the presence of noise and clutter. The PF also models image statistics such as mean and variance of the given data which can be useful in obtaining proper separation of object and backgroun

A novel object tracking algorithm based on compressed sensing and entropy of information

Acknowledgments This research is supported by (1) the Ph.D. Programs Foundation of Ministry of Education of China under Grant no. 20120061110045, (2) the Science and Technology Development Projects of Jilin Province of China under Grant no. 20150204007G X, and (3) the Key Laboratory for Symbol Computation and Knowledge Engineering of the National Education Ministry of China.Peer reviewedPublisher PD

A fast and robust hand-driven 3D mouse

The development of new interaction paradigms requires a natural interaction. This means that people should be able to interact with technology with the same models used to interact with everyday real life, that is through gestures, expressions, voice. Following this idea, in this paper we propose a non intrusive vision based tracking system able to capture hand motion and simple hand gestures. The proposed device allows to use the hand as a "natural" 3D mouse, where the forefinger tip or the palm centre are used to identify a 3D marker and the hand gesture can be used to simulate the mouse buttons. The approach is based on a monoscopic tracking algorithm which is computationally fast and robust against noise and cluttered backgrounds. Two image streams are processed in parallel exploiting multi-core architectures, and their results are combined to obtain a constrained stereoscopic problem. The system has been implemented and thoroughly tested in an experimental environment where the 3D hand mouse has been used to interact with objects in a virtual reality application. We also provide results about the performances of the tracker, which demonstrate precision and robustness of the proposed syste