Jing Xiao

Dr. Jing Xiao, lecturer at School of Computer, Wuhan University. She studied geo-information science at Wuhan University, and received the BSc degree in 2006. After her graduation, she went to the Faculty of Geo-Information Science and Earth Observation, Twente University in the Netherlands for further study. She finished her PhD in May 2013 with the topic of object detection from oblique imagery. In August, she joined the National Engineering Research Center for Multimedia Software (NERCMS) in the school of computer, Wuhan University.

Under the projects of “Efficient coding of big surveillance video data” (National nature science foundation of China) and “QUICK-Quality-of-experience improvement for mobile multimedia across heterogeneous wireless networks” (EU FP7 project), she current research interests include multimedia coding and transmission, analysis of big multimedia data, and computer vision. has published over 20 papers in the journals of IEEE Transaction on Multimedia (TMM), Software：Practice and Experience (SPE), Neurocomputing, etc., and in the conferences of Date Compression Conference (DCC), ACM Multimedia (ACM MM), etc. She is also the reviewer of many international journals and conferences.

Selected Publications：

[1] J. Xiao, R. Hu, L. Liao, Y. Chen, Z. Wang and Z. Xiong, " Knowledge-based Coding of Objects for Multi-source Surveillance Video Data." in IEEE Transactions on Multimedia, vol. 18, no. 9, pp. 1691-1706, 2016.

[2] J. Xiao, Z. Wang, Y. Chen, Y. Chen, L. Liao, J. Xiao, G. Zhan and R. Hu, " A Sensitive Object-Oriented Approach to Big Surveillance Data Compression for Social Security Applications in Smart City." Software: Practice and Experience, 2016, (accepted).

[3] Z. Wang, X. Song, S.Wang, J. Xiao, R. Zhong and R. Hu, "Filling Kinect depth holes via position-guided matrix completion." in Neurocomputing, Jun. 2016.

[4] L. Liao, R. Hu, J. Xiao, G. Zhan, Y. Chen and J. Xiao, “An Analysis-oriented ROI Based Coding Approach on Surveillance Video data.” in Pacific Rim Conference on Multimedia, Xi'an, Sep 15-16, 2016.

[5] L. Hu, Z. Wang, M. Ye, J. Xiao, and R. Hu, “Spatiotemporal Saliency based on Location Prior Model.” in International Joint Conference on Neural Networks, Vancouver, Jul 24-29, 2016.

[6] Q. Wang, Z. Wang, J. Xiao, J. Xiao and W. Li, “Fine-grained Vehicle Recognition in Traffic Surveillance.” in Pacific Rim Conference on Multimedia, Xi'an, Sep 15-16, 2016.

[7] J. Xiao, L. Liao, J. Hu, Y. Chen, and R. Hu, “Exploiting global redundancy in big surveillance video data for efficient coding,” Cluster Computing, vol. 18, no. 2, pp. 531-540, Feb. 2015.

[8] J. Xiao, Y. Chen, L. Liao, J. Hu, and R. Hu, "Global Coding of Multi-Source Surveillance Video Data." in Proc. Data Compression Conf., Snowbird, Apr 7-9, 2015, pp. 33-42.

[9] J. Xiao, M. Gerke, "Building footprint extraction based on radiometric and geometric constraints in airborne oblique images." in International Journal of Image and Data Fusion, vol. 6, no. 3, pp. 270-287, Jul. 2015.