Welcome to the April edition of the IEEE-TCMC (Technical Committee on Multimedia Computing) monthly mailing. TCMC membership is officially determined by signing up with the IEEE Computer Society either with your membership or later through:
http://www.computer.org/services/teca
TCMC home:
http://www.computer.org/portal/web/tcmc
This month’s topics include:
IEEE Computer Society: Technical Committee on Multimedia Computing (CS TCMC)
Held in conjunction with ICME 2012
Date: 11 July 2012
Time: 11:50 – 13:10
Room: 112
CFPs:
IEEE T-SMC:B special issue
IEEE Trans. on Multimedia Special Issue
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Computer Vision for RGB-D Sensors: Kinect and Its Applications Special issue on IEEE Transactions on Systems, Man and Cybernetics – Part B: Cybernectics
Call for Paper:
Depth cameras have been exploited in computer vision for several years, but the high price and the poor quality of such devices have limited their applicability. With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use as an off-the-shelf technology. The complementary nature of the depth and visual (RGB) information in the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision, including object and activity recognition, people tracking, 3D mapping and localization, etc. For a long time, researchers have been challenged by many problems such as detecting and identifying objects/humans in real-world situations. Traditional object segmentation and tracking algorithms based on RGB images are not always reliable when the environment is cluttered or the illumination conditions suddenly change, both of which occur frequently in a real-world setting. However, effectively combining depth and RGB data may provide new solutions to these problems, where object segmentation based on depth information is robust against environmental changes, and the accuracy of object tracking/identification can be improved by considering the depth, motion and appearance information of an object.
Freely available SDKs and posture trackers for the Kinect modeling environments further encourage new solutions to classic problems in computer vision. Compared to conventional computer vision systems (based on RGB images), systems using the Kinect sensor face a number of specific challenges, including characterization of objects based on the RGB-Depth images; correlation between per-pixel depth and RGB information when one of them is missing or corrupted; and, semantic linkage and decision making based on the fused information. Compared to stereo vision or ToF techniques exploiting other depth sensors (i.e., Bumblebee camera or PMD camera), the algorithms designed for the Kinect sensor need to solve additional problems, though the overall depth sensing quality of the Kinect sensor is much better than the other two. These particular problems embody the intelligent computing of per-pixel depth from a noisy and sparse depth point cloud; spatially calibrating and correlating the depth image with the RGB images; data mining from the inhomogeneous depth map; and, designing the illumination patterns for handling light interference effects.
This special issue is specifically dedicated to new algorithms and/or new applications based on the Kinect (or similar RGB-D) sensors. The key outcomes of the special issue will be a better understanding of: * (1) the contributions of this new sensor within the computer vision community, (2) the possible applications of the Kinect sensor, and (3) the key challenges and solutions for research in this domain. Topics of interest include, but are not limited to:
* Object detection and recognition
* Segmentation and clustering
* Human pose estimation
* Human activity recognition and gesture recognition
* 3D scene reconstruction
* Human-computer interaction exploiting depth information
* Robotic vision based on Kinect
* Data mining based on RGB-D information
* Intelligent computing for generating dense depth map
* Decision making for fusing sensors
* Adaptive and learning techniques for a Kinect network (multi-Kinect)
* Transmission and visualization of 3D scenes
* 3D integration and understanding in multimedia applications
* Practical issues of deploying Kinect
* Social and ethical issues of Kinect sensing in public and private spaces
* Use of Kinect to acquire ground truth data in context-aware computing
* Industrial applications
Prospective authors should visit http://www.ieeesmc.org/publications/index.html for information on paper submission. Manuscripts should be submitted using the Manuscript Central system at http://mc.manuscriptcentral.com/smcb-ieee. Please choose “SI: Vision for Kinect” as the manuscript type. Manuscripts will be peer reviewed according to the standard IEEE process.
Important Dates:
Submission of full papers 30 September 2012
Notification to authors 30 January 2013
Submission of revised papers 30 March 2013
Final decision on revised papers 30 May 2013
Tentative publication date Fourth quarter 2013
Guest Editors:
Ling Shao, The University of Sheffield, UK
Jungong Han, CWI, The Netherlands
Dong Xu, Nanyang Technological University, Singapore
Jamie Shotton, Microsoft Research Cambridge, UK
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CALL FOR PAPERS
IEEE Transactions on Multimedia, Special Issue on Socio-Video Semantics
Important Dates
Manuscript submission:
Acceptance/Revision:
Revised manuscript:
Final acceptance:
Final manuscript due:
Tentative publication:
October1, 2013
February 1, 2014
March 15, 2014
May 1, 2014
June 1, 2014
October, 2014
Guest Editors
Dr. Cees G.M. Snoek, Univ. of Amsterdam, the Netherlands, cgmsnoek@uva.nl
Dr. Yu-Gang Jiang, Fudan University, China, ygj@fudan.edu.cn
Dr. Rong Yan, Facebook, USA, rongyan@fb.com
Dr. Jiebo Luo, University of Rochester, USA, jluo@cs.rochester.edu
Prof. Alberto Del Bimbo, Univ. degli Studi Firenze, Italy, delbimbo@dsi.unifi.it
All of a sudden video became social. In just five years, individual and mostly inactive consumers transformed into active and connected prosumers, revolutionaries even, who create, share, and comment on massive amounts of video artifacts all over the world wide web 2.0. In order to make sense of the massive amounts of video content, online social platforms rely on what other people say is in the image, which is known to be ambiguous, overly personalized, and limited. Hence, the lack of semantics currently associated with online video is seriously hampering retrieval, repurposing, and usage. In contrast, academic video sensemaking approaches rely on an analysis of the multimedia content which is important if only to verify what people have said is factually in the video, or for (professional) archives which cannot be shared for crowdsourcing. For sensemaking, exploiting the social multimedia context of video has largely been ignored in the multimedia community. This special issue provides a unique opportunity for high-quality multidisciplinary papers connecting the social context of online video to video sense making.
Researchers from industry are particularly encouraged to submit their work. The issue on socio-video semantics should set the scene for a big leap over the semantic gap. Topics of interest include (but are not limited to):
*? Socio-video content analysis
* Cross-modal (social / visual / audio) socio-video content analysis
* Contextual models for socio-video analysis
* Novel features for socio-video analysis
* Complex event recognition in socio-videos
* Socio-video copy detection
* Content-aware ads optimization in socio-video sharing sites
* Efficient learning and mining algorithms for scalable socio-video content analysis
?* Socio-video browsing and retrieval
* Socio-video retrieval systems
* Socio-video summarization
* Recommender techniques for socio-video browsing
* Mobile socio-video browsing and retrieval
* User-centered interface and system design for socio-video browsing and retrieval
?* Socio-video benchmark construction and open-source software
* Benchmark database construction for socio-video semantic analysis
* Ontology construction for socio-video semantic analysis
* Open-source software libraries for socio-video analysis
Submissions should follow the official guidelines set out by IEEE Transactions on Multimedia, which are located at http://www.ieee.org/organizations/society/tmm/author_info.html. Prospective authors should submit high quality, original manuscripts that have not appeared, nor are under consideration, in any other journals. Manuscripts should be submitted electronically through the online IEEE manuscript submission system at http://mc.manuscriptcentral.com/tmm-ieee/. All papers will be reviewed by at least three expert reviewers in relevant fields. Decision will be made based on the novel scientific and technical contribution of the submissions and their suitability to the interests of this special issue.
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