Journal ArticleDOI
A real-time system for monitoring of cyclists and pedestrians
Janne Heikkilä,Olli Silven +1 more
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A new camera based automatic system that utilizes Kalman filtering in tracking and Learning Vector Quantization for classifying the observations to pedestrians and cyclists is described.About:
This article is published in Image and Vision Computing.The article was published on 2004-07-01. It has received 206 citations till now. The article focuses on the topics: Learning vector quantization & Kalman filter.read more
Citations
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Proceedings ArticleDOI
Robust techniques for background subtraction in urban traffic video
TL;DR: This paper compares various background subtraction algorithms for detecting moving vehicles and pedestrians in urban traffic video sequences, considering approaches varying from simple techniques such as frame differencing and adaptive median filtering, to more sophisticated probabilistic modeling techniques.
Journal ArticleDOI
Intelligent distributed surveillance systems: a review
M. Valera,Sergio A. Velastin +1 more
TL;DR: This survey describes the current state-of-the-art in the development of automated visual surveillance systems to provide researchers in the field with a summary of progress achieved to date and to identify areas where further research is needed.
Journal ArticleDOI
Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art
TL;DR: This paper surveys many existing schemes in the literature of background removal, surveying the common pre-processing algorithms used in different situations, presenting different background models, and the most commonly used ways to update such models and how they can be initialized.
Bibliography of Self-Organizing Map SOM) Papers: 1998-2001 Addendum
TL;DR: This work has provided a keyword index to help finding articles of interest, and additionally a modern automatically constructed variant of a thematic index: a WEBSOM interface to the whole article collection of years 1981-2000.
Journal ArticleDOI
Comparative study of background subtraction algorithms
TL;DR: A comparative study of several state of the art background subtraction methods to provide a solid analytic ground to underscore the strengths and weaknesses of the most widely implemented motion detection methods.
References
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Book
Self-Organizing Maps
TL;DR: The Self-Organising Map (SOM) algorithm was introduced by the author in 1981 as mentioned in this paper, and many applications form one of the major approaches to the contemporary artificial neural networks field, and new technologies have already been based on it.
Journal ArticleDOI
Pfinder: real-time tracking of the human body
TL;DR: 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.
Proceedings ArticleDOI
Real-time tracking of non-rigid objects using mean shift
TL;DR: The theoretical analysis of the approach shows that it relates to the Bayesian framework while providing a practical, fast and efficient solution for real time tracking of non-rigid objects seen from a moving camera.
Book ChapterDOI
Contour Tracking by Stochastic Propagation of Conditional Density
Michael Isard,Andrew Blake +1 more
TL;DR: The Condensation algorithm combines factored sampling with learned dynamical models to propagate an entire probability distribution for object position and shape, over time, and is markedly superior to what has previously been attainable from Kalman filtering.
Proceedings ArticleDOI
Real-time object detection for "smart" vehicles
Dariu M. Gavrila,V. Philomin +1 more
TL;DR: An efficient shape-based object detection method based on Distance Transforms is presented and its use for real-time vision on-board vehicles and some hardware-specific implementations of the proposed method as far as SIMD parallelism is concerned are discussed.