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Designing Category-Level Attributes for Discriminative Visual Recognition ∗

by Felix X. Yu, Liangliang Cao, Rogerio S. Feris, John R. Smith, Shih-fu Chang
"... Attribute-based representation has shown great promises for visual recognition due to its intuitive interpretation and cross-category generalization property. However, human efforts are usually involved in the attribute designing process, making the representation costly to obtain. In this paper, we ..."
Abstract - Cited by 26 (1 self) - Add to MetaCart
, we propose a novel formulation to automatically design discriminative “category-level attributes”, which can be efficiently encoded by a compact category-attribute matrix. The formulation allows us to achieve intuitive and critical design criteria (category-separability, learnability) in a principled

Designing Category-Level Attributes for Discriminative Visual Recognition∗

by unknown authors
"... Attribute-based representation has shown great promises for visual recognition due to its intuitive interpretation and cross-category generalization property. However, human efforts are usually involved in the attribute designing pro-cess, making the representation costly to obtain. In this paper, w ..."
Abstract - Add to MetaCart
, we propose a novel formulation to automatically de-sign discriminative “category-level attributes”, which can be efficiently encoded by a compact category-attribute ma-trix. The formulation allows us to achieve intuitive and crit-ical design criteria (category-separability, learnability) in a

Designing Category-Level Attributes for Discriminative Visual Recognition∗

by unknown authors
"... Attribute-based representation has shown great promis-es for visual recognition due to its intuitive interpretation and cross-category generalization property. However, hu-man efforts are usually involved in the attribute designing process, making the representation costly to obtain. In this paper, ..."
Abstract - Add to MetaCart
, we propose a novel formulation to automatically de-sign discriminative “category-level attributes”, which can be efficiently encoded by a compact category-attribute ma-trix. The formulation allows us to achieve intuitive and crit-ical design criteria (category-separability, learnability) in a

Additional remarks on designing category-level attributes for discriminative visual recognition

by Felix X. Yu, Liangliang Cao, Rogerio S. Feris, John R. Smith, Shih-fu Chang , 2013
"... This is the supplementary material for Designing Category-Level Attributes for Discriminative Visual Recognition [3]. We first provide an overview of the proposed approach in Section 1. The proof of the theorem is shown in Section 2. Additional remarks of the proposed attribute design algorithm are ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
This is the supplementary material for Designing Category-Level Attributes for Discriminative Visual Recognition [3]. We first provide an overview of the proposed approach in Section 1. The proof of the theorem is shown in Section 2. Additional remarks of the proposed attribute design algorithm

Additional Remarks on Designing Category-Level Attributes for Discriminative Visual Recognition∗

by unknown authors
"... This is the supplementary material for Designing Category-Level Attributes for Dis-criminative Visual Recognition [3]. We first provide an overview of the proposed ap-proach in Section 1. The proof of the theorem is shown in Section 2. Additional remarks of the proposed attribute design algorithm ar ..."
Abstract - Add to MetaCart
This is the supplementary material for Designing Category-Level Attributes for Dis-criminative Visual Recognition [3]. We first provide an overview of the proposed ap-proach in Section 1. The proof of the theorem is shown in Section 2. Additional remarks of the proposed attribute design algorithm

Face Recognition: A Literature Survey

by W. Zhao, R. Chellappa, P. J. Phillips, A. Rosenfeld , 2000
"... ... This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into ..."
Abstract - Cited by 1363 (21 self) - Add to MetaCart
into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition,

The PASCAL Visual Object Classes (VOC) challenge

by Mark Everingham, Luc Van Gool, C. K. I. Williams, J. Winn, Andrew Zisserman , 2009
"... ... is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has be ..."
Abstract - Cited by 624 (20 self) - Add to MetaCart
... is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has

High confidence visual recognition of persons by a test of statistical independence

by John G. Daugman - IEEE Trans. on Pattern Analysis and Machine Intelligence , 1993
"... Abstruct- A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a samp ..."
Abstract - Cited by 596 (8 self) - Add to MetaCart
Abstruct- A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a

Visual categorization with bags of keypoints

by Gabriella Csurka, Christopher R. Dance, Lixin Fan, Jutta Willamowski, Cédric Bray - In Workshop on Statistical Learning in Computer Vision, ECCV , 2004
"... Abstract. We present a novel method for generic visual categorization: the problem of identifying the object content of natural images while generalizing across variations inherent to the object class. This bag of keypoints method is based on vector quantization of affine invariant descriptors of im ..."
Abstract - Cited by 984 (14 self) - Add to MetaCart
Abstract. We present a novel method for generic visual categorization: the problem of identifying the object content of natural images while generalizing across variations inherent to the object class. This bag of keypoints method is based on vector quantization of affine invariant descriptors

Shape Matching and Object Recognition Using Shape Contexts

by Serge Belongie, Jitendra Malik, Jan Puzicha - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2001
"... We present a novel approach to measuring similarity between shapes and exploit it for object recognition. In our framework, the measurement of similarity is preceded by (1) solv- ing for correspondences between points on the two shapes, (2) using the correspondences to estimate an aligning transform ..."
Abstract - Cited by 1787 (21 self) - Add to MetaCart
We present a novel approach to measuring similarity between shapes and exploit it for object recognition. In our framework, the measurement of similarity is preceded by (1) solv- ing for correspondences between points on the two shapes, (2) using the correspondences to estimate an aligning
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