Optical wireless is increasingly becoming an attractive option for multi-gigabit-per-second (multi-Gb/s) short range (up to 2 km) links where laying optical fiber is too expensive or impractical. For such links, a tracking scheme is essential to maintain proper pointing of the transceivers at each other to establish error-free communication. For the transmitter, the tracking ensures that a narr...

In multi-cells’ tracking of time-lapse image sequences imaged by optical microscope, problem of tracking active cells correctly is still unsolved. It affects tracking accuracy and speed whether an algorithm can predict the position of the active cells or not. The tracking strategy is guided by Kalman forecast in image Cartesian coordinates systems, which may search target cells via minimizing t...

This paper presents a unified approach to object recognition and object tracking, combining local feature matching with optical flow. Like many traditional recognition algorithms, the one described here implements recognition by matching detected image patches against a database of known objects. This algorithm, however, matches keypoints incrementally, meaning that it only tests a few keypoint...

BACKGROUND Tendon motion, which is commonly observed using ultrasound imaging, is one of the most important features used in tendinopathy diagnosis. However, speckle noise and out-of-plane issues make the tracking process difficult. Manual tracking is usually time consuming and often yields inconsistent results between users. METHODS To automatically track tendon motion in ultrasound images, ...

Stereo vision is a part of the field of computer vision that uses two or more cameras to obtain two or more images from which distance information can be obtained by using the triangulation principle [1]. We can obtain three-dimensional information of static scenes by using this technique. On the other hand, we can use optical flow algorithms for object tracking in two dimensional video sequenc...

Robust Visual Motion Analysis: Piecewise-Smooth Optical Flow and Motion-Based Detection and Tracking

In this paper we present a new active vision technique called zoom tracking. Zoom tracking is the continuous adjustment of a camera’s focal length, to keep a constantsized image of an object moving along the camera’s optical axis. Two methods for performing zoom tracking are presented: a closed-loop visual feedback algorithm based on opticaljlow, and use of depth information obtained from an au...

multiple people detection and tracking is a challenging task in real-world crowded scenes. in this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. we have detected objects with deformable part models and a visual background extractor. in the tracking phase we have used a combination of support vector machine (svm) person-specific classifie...

Since the early 1980s, the Tracker Project at the University of North Carolina at Chapel Hill has been working on wide-area head tracking for virtual and augmented environments. Our long-term goal has been to achieve the high performance required for accurate visual simulation throughout our entire laboratory, beyond into the hallways, and eventually even outdoors. In this article, we present r...