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Object tracking in real time is one of the most important topics in the field of computer Vision. The work undertaken in this dissertation is mainly focused on development of a reliable and robust real time tracking system that can track the object of interest in the video acquired from a stationary or moving camera. The proposed algorithm is a real time algorithm that operates in 25 frames per second...
The concept of active tracking is presented to simulate the characteristics of human vision in intelligent visual surveillance. The Pan/Tilt/Zoom (PTZ) camera is generally used for active tracking. In this paper, we present a novel and effective approach for active object tracking with a PTZ camera, and construct a near real-time system for indoor and outdoor scenes. The tracking algorithm of our...
In panoramic videos, the object movement between adjacent side images leads to deformation and discontinuity, which makes the traditional video tracking approaches insufficient. An effective static object tracking algorithm is proposed in this paper to resolve the tracking problems from the deformation and discontinuity in cubic panorama. The algorithm extends the relevant side images with boundary...
This paper proposes a new interactive augmented reality (AR) application for tracking a remote-control car controlled by players. We present it as a markerless framework for tracking colored remote-control car by integrating a Bayesian classifier into particle filters. This adds the useful abilities of automatic track initialization and recovery from tracking failures in a dynamic background. Furthermore,...
We present an approach for real-time tracking of a non-rigid target with a moving pan-tilt-zoom (PTZ) camera. The tracking of the object and control of the camera is handled by one computer in real time. The main contribution of the paper is method for target representation, localisation and detection, which takes into account both foreground and background properties, and is more discriminative than...
This paper presents methods for vision-based detection and tracking of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. The goal of this research is to develop suitable methods for automatic visual traffic surveillance to perform detection, tracking and traffic parameter estimation of multiple vehicles in real time as well as tackle environment illumination...
Modern automated video analysis systems consist of large networks of heterogeneous sensors. These systems must extract, integrate and present relevant information from the sensors in real-time. This paper addresses some of the major challenges such systems face: efficient video processing for high-resolution sensors; data fusion across multiple modalities; robustness to changing environmental conditions...
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