Journal ArticleDOI
Learning semantic object parts for object categorization
TLDR
This paper proposes to also use co-location and co-activation, together with weak top-down constraints, such as alignment, as guiding principles for learning the appearance of local object parts.About:
This article is published in Image and Vision Computing.The article was published on 2008-01-01. It has received 38 citations till now. The article focuses on the topics: Object model & Method.read more
Citations
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Journal ArticleDOI
Localizing Parts of Faces Using a Consensus of Exemplars
TL;DR: This work presents a novel approach to localizing parts in images of human faces that combines the output of local detectors with a nonparametric set of global models for the part locations based on over 1,000 hand-labeled exemplar images and derives a Bayesian objective function.
Proceedings ArticleDOI
Localizing parts of faces using a consensus of exemplars
TL;DR: A novel approach to localizing parts in images of human faces that combines the output of local detectors with a non-parametric set of global models for the part locations based on over one thousand hand-labeled exemplar images and derives a Bayesian objective function.
Journal ArticleDOI
Semantic hierarchies for image annotation: A survey
TL;DR: It is argued that using structured vocabularies is capital to the success of image annotation, and contributions in the field showing how structures are introduced are surveyed.
Patent
Method and System For Localizing Parts of an Object in an Image For Computer Vision Applications
TL;DR: In this article, a system is provided for localizing parts of an object in an image by training local detectors using labeled image exemplars with fiducial points corresponding to parts within the image.
Journal ArticleDOI
Pedestrian Detection in Far-Infrared Daytime Images Using a Hierarchical Codebook of SURF
TL;DR: The experimental evaluation shows that the proposed pedestrian detector with on-board FIR camera outperforms, in the FIR domain, the state-of-the-art Haar-like Adaboost-cascade, histogram of oriented gradients (HOG)/linear SVM (linSVM) and MultiFtrpedestrian detectors, trained on the FIR images.
References
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Proceedings ArticleDOI
Object recognition from local scale-invariant features
TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
Proceedings ArticleDOI
A Combined Corner and Edge Detector
Chris Harris,Mike Stephens +1 more
TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
Journal ArticleDOI
On combining classifiers
TL;DR: A common theoretical framework for combining classifiers which use distinct pattern representations is developed and it is shown that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision.
Journal ArticleDOI
Recognition-by-Components: A Theory of Human Image Understanding.
TL;DR: Recognition-by-components (RBC) provides a principled account of the heretofore undecided relation between the classic principles of perceptual organization and pattern recognition.
Journal ArticleDOI
Basic objects in natural categories
TL;DR: In this paper, the authors define basic objects as those categories which carry the most information, possess the highest category cue validity, and are the most differentiated from one another, and thus the most distinctive from each other.