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检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013"
656 条 记 录,以下是481-490 订阅
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Volumetric Reconstruction from Multi-Energy Single-View Radiography
Volumetric Reconstruction from Multi-Energy Single-View Radi...
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.10
作者: Sang N. Le Mei Kay Lee Shamima Banu Anthony C. Fang Department of Computer Science School of Computing National University of Singapore Singapore Physical Education and Sports Sciences National Institute of Education Nanyang Technological University Singapore
We address the volumetric reconstruction problem that takes as input a series of orthographic multi-energy X-ray images, producing as output a reconstructed model space consisting of uniform-size mass density voxels. ... 详细信息
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Evaluation of Color Descriptors for Object and Scene recognition
Evaluation of Color Descriptors for Object and Scene Recogni...
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.8
作者: Koen E. A. van de Sande theo Gevers Cees G. M. Snoek University of Amsterdam Amsterdam Netherlands
Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used. To increase illumination invariance and discrimi... 详细信息
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Boosting Ordinal Features for Accurate and Fast Iris recognition
Boosting Ordinal Features for Accurate and Fast Iris Recogni...
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.8
作者: Zhaofeng He Zhenan Sun Tieniu Tan Xianchao Qiu Cheng Zhong Wenbo Dong Center for Biometrics and Security Research National Laboratory of Pattern RecognitionNational Laboratory of Pattern Recognition Chinese Academy and Sciences Beijing China
In this paper, we present a novel iris recognition method based on learned ordinal features. Firstly, taking full advantages of the properties of iris textures, a new iris representation method based on regional ordin... 详细信息
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Human-Assisted Motion Annotation
Human-Assisted Motion Annotation
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.12
作者: Ce Liu William T. Freeman Edward H. Adelson Yair Weiss CSAIL-MIT Israel Hebrew University of Jerusalem Israel
Obtaining ground-truth motion for arbitrary, real-world video sequences is a challenging but important task for both algorithm evaluation and model design. Existing ground-truth databases are either synthetic, such as... 详细信息
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Flat Refractive Geometry
Flat Refractive Geometry
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.12
作者: Tali Treibitz Yoav Y. Schechner Hanumant Singh Department of Electrical Engineering Technion-Israel Institute of Technology Haifa Israel Woods Hole Oceanographic Institution Woods Hole MA USA
While the study of geometry has mainly concentrated on single-viewpoint (SVP) cameras, there is growing attention to more general non-SVP systems. Here we study an important class of systems that inherently have a non... 详细信息
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Unsupervised Feature Selection via Distributed Coding for Multi-view Object recognition
Unsupervised Feature Selection via Distributed Coding for Mu...
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.7
作者: C. Mario Christoudias Raquel Urtasun Trevor Darrell UC Berkeley EECS & ICSI MIT CSAIL USA
Object recognition accuracy can be improved when information from multiple views is integrated, but information in each view can often be highly redundant. We consider the problem of distributed object recognition or ... 详细信息
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Rotation Symmetry Group Detection Via Frequency Analysis of Frieze-Expansions
Rotation Symmetry Group Detection Via Frequency Analysis of ...
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.12
作者: Seungkyu Lee Robert T. Collins Yanxi Liu Department of Computer Science and Engineering Pennsylvania State University USA Dept. of Electrical Engineering The Pennsylvania State University USA
We present a novel and effective algorithm for rotation symmetry group detection from real-world images. We propose a frieze-expansion method that transforms rotation symmetry group detection into a simple translation... 详细信息
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Pair-Activity Classification by Bi-Trajectories Analysis
Pair-Activity Classification by Bi-Trajectories Analysis
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.12
作者: Yue Zhou Shuicheng Yan thomas S. Huang Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign USA Department of Electrical and Computer Engineering National University of Singapore Singapore
In this paper, we address the pair-activity classification problem, which explores the relationship between two active objects based on their motion information. Our contributions are three-fold. First, we design a se... 详细信息
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Kernel-based learning of cast shadows from a physical model of light sources and surfaces for low-level segmentation
Kernel-based learning of cast shadows from a physical model ...
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.3
作者: Nicolas Martel-Brisson Andre Zaccarin Computer Vision and Systems Laboratory Department of Electrical and Computer Engineering Laval University QUE Canada
In background subtraction, cast shadows induce silhouette distortions and object fusions hindering performance of high level algorithms in scene monitoring. We introduce a nonparametric framework to model surface beha... 详细信息
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Scene Classification with Low-dimensional Semantic Spaces and Weak Supervision
Scene Classification with Low-dimensional Semantic Spaces an...
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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.1
作者: Nikhil Rasiwasia Nuno Vasconcelos Department of Electrical and Computer Engineering University of California San Diego USA
A novel approach to scene categorization is proposed. Similar to previous works of [11, 15, 3, 12], we introduce an intermediate space, based on a low dimensional semantic "theme" image representation. Howev... 详细信息
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