Journal ArticleDOI
Video object tracking using adaptive Kalman filter
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TLDR
The proposed method has the robust ability to track theMoving object in the consecutive frames under some kinds of real-world complex situations such as the moving object disappearing totally or partially due to occlusion by other ones, fast moving object, changing lighting, changing the direction and orientation of the movingobject, and changing the velocity of moving object suddenly.About:
This article is published in Journal of Visual Communication and Image Representation.The article was published on 2006-12-01. It has received 314 citations till now. The article focuses on the topics: Video tracking & Kalman filter.read more
Citations
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Journal ArticleDOI
Eye-wearable head-mounted tracking and gaze estimation interactive machine system for human–machine interface:
TL;DR: The proposed eye-tracking algorithms can provide a low-complexity solution with high accuracy, precision, and speed and can be used in headsets for virtual reality, auxiliary equipment, interactive machine, and human–machine interface applications.
Dissertation
Event-driven traffic ticketing system
TL;DR: This chapter discusses algorithms used in the development of knowledge representation systems and some of the techniques used in their development.
Proceedings ArticleDOI
Motion-compensated optical coherence tomography using envelope-based surface detection and Kalman-based prediction
TL;DR: Implementing such motion compensation into clinical OCT systems may improve the reliability of objective and quantitative information that can be extracted from OCT measurements, particularly noticeable in multilayered tissues, while utilizing the novel technique.
Journal ArticleDOI
Video Stabilization and Region-of-Interest Tracking in Cardiac MRI Domain
TL;DR: This work suggests a novel algorithm for CMRI tracking and stabilization, inspired by cortical mechanisms of the human visual system (HVS), for both edge and region pathways, which manages to stabilize perfusion CMRI slice for long burst of frames, which indicates the potential for allowing a better medical diagnosis.
Book ChapterDOI
Research on Multi-Source Fusion Based Seamless Indoor/Outdoor Positioning Technology
TL;DR: This paper proposes system architecture for the integration of WLAN fingerprinting, visual positioning, baroceptor-derived altitude estimation and GNSS for seamless indoor/outdoor positioning for vehicles and pedestrians and shows that multi-source fusion has an accuracy level of better than 1 m (outdoor)/3 m (indoor), hence capable of meeting users’ demand for seamlessly indoor/ outdoor positioning.
References
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BookDOI
An Introduction to the Kalman Filter
Greg Welch,Gary Bishop +1 more
TL;DR: The discrete Kalman filter as mentioned in this paper is a set of mathematical equations that provides an efficient computational (recursive) means to estimate the state of a process, in a way that minimizes the mean of the squared error.
Journal ArticleDOI
A Survey of Computer Vision-Based Human Motion Capture
Thomas B. Moeslund,Erik Granum +1 more
TL;DR: A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented, with a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition.
Proceedings ArticleDOI
Moving target classification and tracking from real-time video
TL;DR: An end-to-end method for extracting moving targets from a real-time video stream, classifying them into predefined categories according to image-based properties, and then robustly tracking them is described.
Journal ArticleDOI
Robust online appearance models for visual tracking
TL;DR: A framework for learning robust, adaptive, appearance models to be used for motion-based tracking of natural objects to provide robustness in the face of image outliers, while adapting to natural changes in appearance such as those due to facial expressions or variations in 3D pose.
Book ChapterDOI
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
TL;DR: A probabilistic method for tracking 3D articulated human figures in monocular image sequences that relies only on a frame-to-frame assumption of brightness constancy and hence is able to track people under changing viewpoints, in grayscale image sequences, and with complex unknown backgrounds.