This paper presents a hybrid approach to 3D arm motion tracking for tele-rehabilitation applications. A particle filter (PF) algorithm is adopted in the proposed system to fuse data from inertial and visual sensors in a probabilistic manner. Multi-modal distributions of system states are propagated

in indoor surveillance

This paper describes SwarmArt, a collaborative project be-tween computer science and art, which resulted in two in-stallations of interactive art that incorporates swarm intel-ligence. We describe the scientific context of the artwork, technical details of the video system, through which user interaction is controlled, and the realization of the swarm-based simulations, which were projected onto a large screen. Finally, we explain and illustrate our two recent SwarmArt installations in a Calgary gallery.

Our goal is to develop a visual monitoring system that passively observes moving objects in a site and learns patterns of activity from those observations. For extended sites, the system will require multiple cameras. Thus, key elements of the system are motion tracking, camera coordination

first present the integration of a single robot behavioral model with multiple actions into our dynamic Bayesian probabilistic tracking algorithm. We then extend to multiple motion tracking models corresponding to known multi-robot coordination plans or from multi-robot communication. We evaluate our

albeit well-understood problems in computer vision. Existing softwares that combine the two approaches to perform stereo motion tracking typically employ complicated and computationally expensive procedures. The purpose of this study is to create a simple and effective solution capable of combining

The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns

In this paper, we are presenting our results for motion tracking animals in stabling. This system was used in order to record the behavior of pigs in stabling.

its effectiveness for precision motion tracking.

The main challenge in articulated body motion tracking is the large number of degrees of freedom (around 30) to be recovered. Search algorithms, either deterministic or stochastic, that search such a space without constraint, fall foul of exponential computational complexity. One approach