Content Gazette - February 2020 - 10

(Contents Continued from Front Cover)
Display Technology for Multimedia
QoE Analysis of Dense Multiview Video With Head-Mounted Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Cubelos, P. Carballeira, J. Guti´errez, and N. Garc´ıa

69

Green Multimedia Communications and Computing
Efficient and Secure Image Communication System Based on Compressed Sensing for IoT Monitoring Applications. . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. Li, G. Wen, Z. Wang, and Y. Yang

82

Video Surveillance and Semantic Analysis
Deep Position-Sensitive Tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Zha, T. Ku, Y. Li, and P. Zhang
Using Blockchain for Improved Video Integrity Verification . . . . . . . . . . . . . . . . . . . . . . . S. Ghimire, J. Y. Choi, and B. Lee

96
108

Multimodal Human-machine Interfaces and Interaction
Locally Confined Modality Fusion Network With a Global Perspective for Multimodal Human Affective Computing . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Mai, S. Xing, and H. Hu

122

Multimodal Perception, Integration, and Multisensory Fusion
Gestures In-The-Wild: Detecting Conversational Hand Gestures in Crowded Scenes Using a Multimodal Fusion of Bags
of Video Trajectories and Body Worn Acceleration . . . . . . . . . . . . . . . . . L. Cabrera-Quiros, D. M. J. Tax, and H. Hung
A Multi-Task Neural Approach for Emotion Attribution, Classification, and Summarization . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G. Tu, Y. Fu, B. Li, J. Gao, Y.-G. Jiang, and X. Xue
RGB-T Image Saliency Detection via Collaborative Graph Learning . . . Z. Tu, T. Xia, C. Li, X. Wang, Y. Ma, and J. Tang
Multimedia Search and Retrieval
Multi-Pathway Generative Adversarial Hashing for Unsupervised Cross-Modal Retrieval . . . . . . . . . J. Zhang and Y. Peng
Neighbourhood Structure Preserving Cross-Modal Embedding for Video Hyperlinking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Hao, C.-W. Ngo, and B. Huet

Distributed/Cooperative Networks and Communications
Dynamic Spectrum Access for Multimedia Transmission Over Multi-User, Multi-Channel Cognitive Radio Networks
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . X.-L. Huang, X.-W. Tang, and F. Hu

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Deep Learning for Multimedia Analysis
Loopy Residual Hashing: Filling the Quantization Gap for Image Retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Bai, Z. Li, B. Ni, M. Wang, X. Yang, C. Hu, and W. Gao
STAT: Spatial-Temporal Attention Mechanism for Video Captioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Yan, Y. Tu, X. Wang, Y. Zhang, X. Hao, Y. Zhang, and Q. Dai
Deep0Tag: Deep Multiple Instance Learning for Zero-Shot Image Tagging . . . . . . . . . S. Rahman, S. Khan, and N. Barnes
A Novel Convolutional Neural Network for Image Steganalysis With Shared Normalization . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Wu, S.-H. Zhong, and Y. Liu

256

Deep Learning for Multimedia Processing
The Role of the Input in Natural Language Video Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Cascianelli, G. Costante, A. Devo, T. A. Ciarfuglia, P. Valigi, and M. L. Fravolini

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