******************************************************************************
Apologies if you receive multiple copies of this announcement
******************************************************************************

Special Issue on “Methods and Tools for Ground Truth Collection in Multimedia Applications” of the Multimedia Tools and Applications (MTAP) Journal, Springer

Important Dates
========================

Submission of papers: 30 July 2012
Acceptance/Revision notification: 30 October 2012
Revised manuscript due: 30 November 2012
Final acceptance notification: 15 January 2013
Final manuscript due: 15 March 2013
Tentative publication: May 2013

Special Issue Description

========================

The importance of having multimedia database containing high quality ground truth annotations generated by humans for a variety of multimedia applications is widely recognized. Indeed, one of the most significant efforts during the evaluation process is represented by the development of accurate truth and comparing this truth to the decision of applications. However, the cost of providing labeled data, which implies asking a human to examine multimedia and provide labels, becomes impractical as datasets to be labeled grow.

The multimedia community has proposed in the years several datasets, which are too small and targeted to specific tasks (e.g. for object detection and recognition, text retrieval, etc.). To build up large scale general purpose datasets, recently, methods that exploit the collaborative effort of a large population of users annotators (e.g. LabelMe, CalTech 101 and 256, Trecvid) have been devised. However, the creation of a common and large scale ground truth to train, test and evaluate algorithms for multimedia processing is still a major concern. The most obvious way to achieve a common ground truth would be to unify all the existing efforts; unfortunately, the absence of a standard both in data representation and in file format impedes such an integration. Moreover, the research in ground truth labeling still lacks also both in developing user-oriented tools and in automatic methods for supporting annotators in the ground truth labeling task. In fact, tools for ground truth annotation must be user-oriented, providing visual interfaces and methods that are able to guide and speed-up the process of ground truth creation. Under this scenario, multimedia processing methods and collaborative methods play a crucial role in helping annotators to accomplish their task as efficiently as possible.

This special issue intends to promote multidisciplinary research between different research fields (e.g. multimedia, computer vision, speech processing, text retrieval, and HCI) on the construction and analysis of user-oriented tools, collaborative methods and data processing approaches for supporting automatic or semi-automatic ground truth data collection and methods for ground truth data sharing and representation.

The special issue will specifically address the development of: multimedia processing methods for supporting automatic ground truth generation, methods and tools for combining and comparing ground truth labeled by multiple users in any field of multimedia where ground truth is required, interfaces (adaptive, proactive, mobile, web-based) for collecting ground truth, methods for data representation and integration, interoperability middleware, features, algorithms, and tools.

Topics
========================

Submissions are encouraged, but not limited, to the following topics:

- Methods supporting automatic or semi-automatic machine tagging for ground truth data annotation;
- Automatic methods for comparing and combining multi-users ground truth annotation;
- Visual interfaces (adaptive, multimodal, collaborative) for ground truth collection;
- Comparative analysis of existing tools and datasets;
- Web Semantic approaches for ground truth representation and sharing
- Tools and Applications for ground truth labeling in object detection, object recognition, event detection, behavior understanding and image segmentation, text retrieval and speech processing.

Paper Submission, Review, and Publication

=================================

Submissions   must include   new, unpublished, original research. All papers must be written in English. The submissions will be reviewed in a double-blind procedure by   at least three expert reviewers to guarantee high quality standard.

Papers must be submitted electronically at https://www.editorialmanager.com/mtap/ and selecting the special issue “Ground Truth Collection in Multimedia Applications”.


Guest Editors
========================

Concetto Spampinato,  [log in to unmask], University of Catania – Italy.
Bas Boom, [log in to unmask] , University of Edinburgh – UK
Jiyin He,  [log in to unmask],  CWI, The Netherlands




To unsubscribe from the MM-INTEREST list, click the following link:
http://listserv.acm.org/SCRIPTS/WA-ACMLPX.EXE?SUBED1=MM-INTEREST&A=1