[Imageworld] Call for Papers: IEEE Workshop on Three Dimensional Information Extraction for Video Analysis and Mining (CVPR 2010)

[Arturo Donate]

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Call for Papers:  IEEE Workshop on Three Dimensional Information Extraction
for Video Analysis and Mining (in conjunction with CVPR 2010)
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**Important dates**:
Deadline:  March 14
Notification:  April 4
Camera-ready:  April 11
Workshop:  June 14

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For more details, please see our website at:
http://ww2.cs.fsu.edu/~donate/public/workshop/

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With the availability of large video databases, video analysis and
mining has become an active
of research involving the computer vision, image processing, and
information retrieval communities.
Many algorithms have been proposed and numerous systems have been
implemented, most of which
are based on extrinsic representations of scenes by extracting and
utilizing image features from video
frames.

The goal of this line of research is to extract the three dimensional
structure of the scene observed in
a video, and use it to improve the performance on various video
analysis tasks. Such tasks may include
shot-boundary detection, scene segmentation, video summarization,
content-based video retrieval,
and so on. Since video frames are two dimensional projections of three
dimensional scenes, intrinsic
three dimensional representations (as well as associated methods)
should provide more robust and
meaningful information to improve the performance of these video analysis tasks.

Intrinsic three dimensional information in videos, however, has not
been widely employed. Extracting
three dimensional information is not only a computationally intensive
task, but the problem contains
many other inherent challenges. Such challenges include dealing with
3D information extraction from a
single view of a scene (as opposed to using a stereo camera), unknown
camera calibration information
of a scene, designing methods robust enough to deal with arbitrary
object and camera motions, etc.

The goals of the workshop are mainly two folds. First, to promote the
computer vision community
to adopt its expertise on video analysis tasks; these tasks involve
all core image analysis and computer
vision problems, and provide a good testbed for testing algorithms.
Second, to act as a bridge among
several communities to facilitate collaborations and cross-cutting
research topics that are mutually beneficial.

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Papers describing novel and original research are solicited in the
areas related to video analysis and 3D
information extraction. Some topics include (but are certainly not limited to):

•  New 3D information extraction techniques for video analysis.
•  Mathematical models of 3D objects for video analysis
•  Efficient and effective representations of 3D video data for
retrieving and indexing.
•  Video analysis and mining systems, and applications that rely on 3D
information
•  Methods for extracting 3D information from videos.
•  3D feature descriptors from 2D video data.
•  Camera localization from videos.
•  Content-based video searching/retrieving using 3D data.
•  Shot/scene boundary detection incorporating intrinsic 3D information
•  3D motion analysis in videos.

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Organizing Committee:
•   Bir Bhanu, University of California, Riverside
•   Arturo Donate, Florida State University
•   Xiuwen Liu, Florida State University
•   Igor Kozintsev, Intel Labs, Intel Corporation

Program Committee:
•   J. K. Aggarwal, The University of Texas at Austin
•   Bir Bhanu, University of California, Riverside
•   Andrew Davison, Imperial College London
•   Arturo Donate, Florida State University
•   Richard Hartley, Australian National University
•   Omar Javed, ObjectVideo Inc.
•   Rangachar Kasturi, University of South Florida
•   Igor Kozintsev, Intel Labs, Intel Corporation
•   Xiuwen Liu, Florida State University
•   Yaser Sheikh, Carnegie Mellon University
•   Dan Schonfeld, University of Illinois at Chicago
•   Dacheng Tao, Nanyang Technological University
•   George Toderici, Google, Inc.