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» Probabilistic Object Tracking Using Multiple Features
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PAMI
2008
175views more  PAMI 2008»
13 years 9 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...
PAMI
2011
12 years 12 months ago
Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
Yang Wang 0003, Greg Mori
FLAIRS
2006
13 years 10 months ago
Design, Implementation and Performance Analysis of Pervasive Surveillance Networks
Pervasive surveillance implies the continuous tracking of multiple targets as they move about the monitored region. The tasks to be performed by a surveillance system are expresse...
Amit Goradia, Zhiwei Cen, Clayton Haffner, Ning Xi...
ISER
1999
Springer
114views Robotics» more  ISER 1999»
14 years 1 months ago
Continuous Probabilistic Mapping by Autonomous Robots
In this paper, we present a new approach for continuous probabilistic mapping. The objective is to build metric maps of unknown environments through cooperation between multiple au...
Jesús Salido Tercero, Christiaan J. J. Pare...
EVOW
2008
Springer
13 years 11 months ago
Artificial Creatures for Object Tracking and Segmentation
We present a study on the use of soft computing techniques for object tracking/segmentation in surveillance video clips. A number of artificial creatures, conceptually, "inhab...
Luca Mussi, Stefano Cagnoni