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Final
Program for June 24
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08:30-08:35
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Opening
Remarks
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08:35-09:15
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Invited
Talk by Dr. Harry Shum, Microsoft Research, USA
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09:15-09:45
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Large
Scale Medical Image Search via Unsupervised PCA Hashing
Xiang Yu , Shaoting Zhang, Bo Liu, Lin Zhong, Dimitris Metaxas,
Rutgers University, USA
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09:45-10:15
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Big
Data Scalability Issues in WAAS
Jan Prokaj, Xuemei Zhao,
Jongmoo Choi, Gerard Medioni, University of Southern California, USA
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10:15-10:45
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Morning Break
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10:45-11:25
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Invited
Talk by Prof. Shih-Fu Chang, Columbia University, USA
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11:25-11:55
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Iterative
reconstruction of large scenes using heterogeneous feature tracking
Rohith
MV, Stephen Rhein, Guoyu Lu,
Andrew
R. Mahoney, Hajo Eickeny, University of Alaska Fairbanks, USA
G.
Carleton Ray University of Virginia, USA
Chandra
Kambhamettu, University of Delaware, USA
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12:00-13:30
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Lunch (provided)
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13:30-14:00
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Learning
Regularized, Query-dependent Bilinear Similarities for Large Scale Image
Retrieval
Zhanghui Kuang, Jian Sun,
Kenneth Wong, University of Hong Kong, Hong Kong
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14:00-14:30
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Lost
but Found? Harnessing the Internet for Photometric Completion
Pratyush Sahay,
Rajagopalan Ambasamudram, IIT Madras, India
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14:30-15:00
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Duplicate
Discovery on 2 Billion Internet Images
Xin-Jing Wang, Lei Zhang,
Ce Liu, Microsoft Research Asia, China
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15:00-15:30
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Efficient
Category Mining by Leveraging Instance Retrieval
Mayank Juneja, Abhinav
Goel, CV Jawahar, IIIT Hyderabad, India
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15:30-15:55
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Afternoon Break
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15:55-16:25
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Peak
Valley Edge Patterns: A New Descriptor for Biomedical Image Indexing and
Retrieval
Subrahmanyam Murala, QM
Wu, University of Windsor, Canada
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16:25-16:55
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Decoupling
Sparse Coding with Fusion of Fisher Vector and Scalable SVMs for
Large-scale Visual Recognition
Zhengping Ji, Los Alamos
National Laboratory, USA
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16:55-17:25
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Exploiting
Unlabeled Ages for Aging Pattern Analysis on A Large Database
Guodong Guo, Chao Zhang,
West Virginia University, USA
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17:25-17:45
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Closing
remarks, round-table discussion
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Important
Dates
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Submission deadline extended:
April 11, 2013, 11:59pm. EST
Author
notification: April 29, 2013
Final paper
deadline: May 10, 2013 @10 AM PDT
Workshop date:
June 24th 2013
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Distinguished
Speakers:
Harry Shum ,
Microsoft Research
Shih-Fu Chang , Columbia
University
and more …
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Reviews for submitted papers
are now available on CMT.
All the selected papers will be included
in Proceedings of CVPR 2013 (CVPR-DVD) and made available on IEEE eXplore.
Introduction
Large scale image
analysis has attracted considerable amount of interest in the computer vision,
robotics, medical imaging and remote sensing communities. Big Data Computer
Vision (BDCV) 2013 (in conjunction with CVPR 2013) is the first of several
future planned workshops with emphasis on novel scalable solutions for big
data generated by sensors and devices.
This workshop focuses on scalable image analysis algorithms, methods and
solutions for addressing the ever increasing amounts of big image data that
are dynamic, complex, multidimensional and multi-modal. This workshop covers
all aspects of large scale vision and will be the venue for papers which
potentially involve interdisciplinary researchers from all the fields
connected to large-scale image analysis.
Big Data Image Analysis Methods Include but are not limited to:
(a) structure from motion and multi-view stereo techniques
towards large scale environments,
(b) recognition and retrieval techniques in large image
datasets,
(c) internet computer vision, and
(d) emergence of big data resulting from the explosion of multimedia
content on the web.
The workshop will foster
in-depth discussions on Big Data Analysis via oral and poster paper tracks
supported by sessions on selected related topics. Big Data Computer Vision is
held in conjunction with CPVR 2013 and will take place at the Oregon
Convention Center in Portland, Oregon.
Overall Meeting Sponsors
 
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