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CVPR
2007
IEEE
14 years 9 months ago
Unsupervised Segmentation of Objects using Efficient Learning
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
SDM
2007
SIAM
146views Data Mining» more  SDM 2007»
13 years 9 months ago
ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...
CVPR
2007
IEEE
14 years 9 months ago
Online Detection of Fire in Video
This paper describes an online learning based method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. Our fire detection method...
A. Enis Çetin, B. Ugur Töreyin

Publication
353views
13 years 8 months ago
Online Multi-Person Tracking-by-Detection from a Single, Uncalibrated Camera
In this paper, we address the problem of automatically detecting and tracking a variable number of persons in complex scenes using a monocular, potentially moving, uncalibrated ca...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
ICCV
2003
IEEE
14 years 9 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona