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» Structured Learning and Prediction in Computer Vision
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CVPR
2007
IEEE
14 years 10 months ago
Composite Models of Objects and Scenes for Category Recognition
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
David J. Crandall, Daniel P. Huttenlocher
CVPR
2008
IEEE
14 years 10 months ago
A hierarchical and contextual model for aerial image understanding
In this paper we present a novel method for parsing aerial images with a hierarchical and contextual model learned in a statistical framework. We learn hierarchies at the scene an...
Jake Porway, Kristy Wang, Benjamin Yao, Song Chun ...
CVPR
2008
IEEE
14 years 10 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
ICCV
2009
IEEE
15 years 29 days ago
Modelling Activity Global Temporal Dependencies using Time Delayed Probabilistic Graphical Model
We present a novel approach for detecting global behaviour anomalies in multiple disjoint cameras by learning time delayed dependencies between activities cross camera views. Sp...
Chen Change Loy, Tao Xiang and Shaogang Gong
CVPR
2010
IEEE
14 years 4 months ago
Cascade Object Detection with Deformable Part Models
We describe a general method for building cascade classifiers from part-based deformable models such as pictorial structures. We focus primarily on the case of star-structured mod...
Pedro Felzenszwalb, Ross Girshick, David McAlleste...