Multimedia Data Fusion

Multimedia data is widely used in the world such as image, video, text, and audio. For obtaining better sensing performance, research on multimedia data fusion (MDF) is active and extensive around the world. In medical systems, a body part could be imagedwith different sensors such as computed tomography and magnetic resonance imaging. In video surveillance, the interest is in the identification, recognition, and tracking of people by numerous cameras. All of these cases illustrate the importance of MDF in real-life applications. A number of mathematical methods have been researched in MDF such as statistics, fuzzy mathematical, stochastic differential theory, and computational methods. As a special issue, we aim to reflect on the current and future theory and application of MDF in the following aspects: sensor fusion in multimedia medical data, sensor registration in 3D multimedia data, sensor selection for optimal sensor fusion, performance evaluation of the data fusion algorithms, joint data registration and fusion algorithms and the application of multimedia data fusion.

[1]  Hyun Seung Yang,et al.  Robust People Tracking Using an Adaptive Sensor Fusion between a Laser Scanner and Video Camera , 2013, Int. J. Distributed Sens. Networks.

[2]  Shu-li Sun,et al.  Multi-sensor optimal information fusion Kalman filters with applications , 2004 .

[3]  Chinmay Hegde,et al.  Joint Manifolds for Data Fusion , 2010, IEEE Transactions on Image Processing.

[4]  Thomas S. Huang,et al.  Multi-metric learning for multi-sensor fusion based classification , 2013, Inf. Fusion.

[5]  Francesco Bullo,et al.  Optimal sensor placement and motion coordination for target tracking , 2006, Autom..

[6]  Yoshinobu Sato,et al.  A similarity measure for nonrigid volume registration using known joint distribution of targeted tissue: Application to dynamic CT data of the liver , 2003, Medical Image Anal..

[7]  M. Graef,et al.  Application of joint histogram and mutual information to registration and data fusion problems in serial sectioning microstructure studies , 2009 .

[8]  Zhi Tian,et al.  Performance evaluation of track fusion with information matrix filter , 2002 .

[9]  Mohan S. Kankanhalli,et al.  Multimodal fusion for multimedia analysis: a survey , 2010, Multimedia Systems.

[10]  Thompson Sarkodie-Gyan,et al.  An approach to sensor fusion in medical robots , 2009, 2009 IEEE International Conference on Rehabilitation Robotics.

[11]  Bernadette Dorizzi,et al.  A pervasive multi-sensor data fusion for smart home healthcare monitoring , 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

[12]  Franck Marzani,et al.  Registration of 3D and Multispectral Data for the Study of Cultural Heritage Surfaces , 2013, Sensors.

[13]  Kouki Nagamune.  Development of force measurement system by embedding force sensor to insert of knee prosthesis , 2010, 2010 World Automation Congress.

[14]  Sulema Aranda,et al.  On Optimal Sensor Placement and Motion Coordination for Target Tracking , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[15]  Sudharman K. Jayaweera,et al.  Bayesian Fusion Performance and System Optimization for Distributed Stochastic Gaussian Signal Detection Under Communication Constraints , 2007, IEEE Transactions on Signal Processing.

[16]  Felix Bollenbeck,et al.  Joint Registration and Segmentation of Histological Volume Data by Diffusion-Based Label Adaption , 2010, 2010 20th International Conference on Pattern Recognition.

[17]  Ramanarayanan Viswanathan,et al.  Optimal Decision Fusion in Multiple Sensor Systems , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[18]  Guido Gerig,et al.  Building spatiotemporal anatomical models using joint 4-D segmentation, registration, and subject-specific atlas estimation , 2012, 2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis.

[19]  Yunmin Zhu,et al.  Optimal dimensionality reduction of sensor data in multisensor estimation fusion , 2005, IEEE Trans. Signal Process..