Pfinder: real-time tracking of the human body
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TLDR
Pfinder is a real-time system for tracking people and interpreting their behavior that uses a multiclass statistical model of color and shape to obtain a 2D representation of head and hands in a wide range of viewing conditions.Abstract:
Pfinder is a real-time system for tracking people and interpreting their behavior. It runs at 10 Hz on a standard SGI Indy computer, and has performed reliably on thousands of people in many different physical locations. The system uses a multiclass statistical model of color and shape to obtain a 2D representation of head and hands in a wide range of viewing conditions. Pfinder has been successfully used in a wide range of applications including wireless interfaces, video databases, and low-bandwidth coding.read more
Citations
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Journal ArticleDOI
Mean shift: a robust approach toward feature space analysis
Dorin Comaniciu,Peter Meer +1 more
TL;DR: It is proved the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density.
Proceedings ArticleDOI
Adaptive background mixture models for real-time tracking
Chris Stauffer,W.E.L. Grimson +1 more
TL;DR: This paper discusses modeling each pixel as a mixture of Gaussians and using an on-line approximation to update the model, resulting in a stable, real-time outdoor tracker which reliably deals with lighting changes, repetitive motions from clutter, and long-term scene changes.
Journal ArticleDOI
Object tracking: A survey
TL;DR: The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends to discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects.
Journal ArticleDOI
Kernel-based object tracking
TL;DR: A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed, which employs a metric derived from the Bhattacharyya coefficient as similarity measure, and uses the mean shift procedure to perform the optimization.
Journal ArticleDOI
Learning patterns of activity using real-time tracking
Chris Stauffer,W.E.L. Grimson +1 more
TL;DR: This paper focuses on motion tracking and shows how one can use observed motion to learn patterns of activity in a site and create a hierarchical binary-tree classification of the representations within a sequence.
References
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Proceedings ArticleDOI
Real-time American Sign Language recognition from video using hidden Markov models
Thad Starner,Alex Pentland +1 more
TL;DR: A real-time HMM-based system for recognizing sentence level American Sign Language (ASL) which attains a word accuracy of 99.2% without explicitly modeling the fingers.
Book
A Source Book of Gestalt Psychology
TL;DR: The authors provide an excellent overview of early investigations into areas now included in cognitive psychology, including colour and colour theory, sense-perception, speech, memory, reasoning and language, as well as contemporary approaches to Gestalt psychology.
Journal ArticleDOI
Recursive estimation of motion, structure, and focal length
Ali Azarbayejani,Alex Pentland +1 more
TL;DR: Presents a formulation for recursive recovery of motion, pointwise structure, and focal length from feature correspondences tracked through an image sequence, yielding a stable and accurate estimation framework which applies uniformly to both true perspective and orthographic projection.
Book ChapterDOI
Visual tracking of high DOF articulated structures: an application to human hand tracking
James M. Rehg,Takeo Kanade +1 more
TL;DR: A model-based hand tracking system, called DigitEyes, that can recover the state of a 27 DOF hand model from ordinary gray scale images at speeds of up to 10 Hz is described.
Journal ArticleDOI
Towards model-based recognition of human movements in image sequences
TL;DR: A model-based approach for the recognition of pedestrians is introduced and the human body is represented by a 3D-model consisting of cylinders, whereas for modelling the movement of walking the authors use data from medical motion studies.