We present a demonstrated and commercially viable self-tracker, using robust software that fuses data from inertial and vision sensors. Compared to infrastructurebased trackers, self-trackers have the advantage that objects can be tracked over an extremely wide area, without the prohibitive cost of an extensive network of sensors or emitters to track them. So far most AR research has focused on...

To improve load balancing in NoCs several techniques exists in literature like Regional Congestion Awareness (RCA) and similar techniques. Also there are some techniques based on output port selection like count of free virtual channels, count of fluid buffers, buffer occupancy time at reachable downstream neighbors and flit flow history based algorithm named as Tracker. Among these techniques,...

Extendedor long-range tracking effectiveness is crucial for the automation of manufacturing systems. In this paper, we conceptualize and develop a prototype long-range hybrid tracker based on a combination of a laser tracker and a magnetic tracker and apply the concept to the following two applications: 1) extended-range human motion tracking on factory floors and 2) factory floor object recons...

Real-time tracking algorithms often suffer from low accuracy and poor robustness when confronted with difficult, real-world data. We present a tracker that combines 3D shape, color (when available), and motion cues to accurately track moving objects in real-time. Our tracker allocates computational effort based on the shape of the posterior distribution. Starting with a coarse approximation to ...

This paper presents a new algorithm to track mobile objects in different scene conditions. The main idea of the proposed tracker includes estimation, multi-features similarity measures and trajectory filtering. A feature set (distance, area, shape ratio, color histogram) is defined for each tracked object to search for the best matching object. Its best matching object and its state estimated b...

Many trackers have been proposed for tracking objects individually in previous research. However, it is still difficult to trust any single tracker over a variety of circumstances. Therefore, it is important to estimate how well each tracker performs and fusion the tracking results. In this paper, we propose a symbiotic black-box tracker (SBB) that learns only from the output of individual trac...

One of the crucial components of dialog system is the dialog state tracker, which infers user’s intention from preliminary speech processing. Since the overall performance of the dialog system is heavily affected by that of the dialog tracker, it has been one of the core areas of research on dialog systems. In this paper, we present a dialog state tracker that combines a generative probabilisti...

The photovoltaic sun tracker allows us to increase the energy production. The sun tracker considered in this study has two degrees of freedom (2-DOF) and especially specified by the lack of sensors. In this way, the tracker will have as a set point the sun position at every second during the day for a period of five years. After sunset, the tracker goes back to the initial position (which of su...

The results of the CMS tracker alignment analysis are presented using the data from cosmic tracks, optical survey information, and the laser alignment system at the Tracker Integration Facility at CERN. During several months of operation in the spring and summer of 2007, about five million cosmic track events were collected with a partially active CMS Tracker. This allowed us to perform first a...

We present a framework for improving probabilistic tracking of an extended object with a set of model points. The framework combines the tracker with an on-line performance measure and a correction technique. We correlate model point trajectories to improve on-line the accuracy of a failed or an uncertain tracker. A model point tracker gets assistance from neighboring trackers whenever a degrad...