导师姓名：高陈强
性别：男
人气指数：535

所属院校：重庆邮电大学
所属院系：通信与信息工程学院
职称：教授
导师类型：博导
招生专业：
研究领域： 红外小目标检测、红外图像分析、监控视频分析、目标检测与跟踪、行为识别、事件检测、深度学习
研究领域： 红外小目标检测、红外图像分析、监控视频分析、目标检测与跟踪、行为识别、事件检测、深度学习 [收起]




通讯方式 :
电子邮件：gaocq@cqupt.edu.cn
通讯地址：逸夫科技楼YF416


个人简述 :
高陈强，男，教授, 博导，1981年8月生于重庆，中国地质大学（武汉）工学学士，华中科技大学工学博士，美国卡内基梅隆大学（CMU）博士后，2011年获重庆市高等学校骨干教师人才资助计划。2009年8月至今，在重庆邮电大学信号与信息处理重庆市重点实验室从事科研和教学工作。作为主持人主持国家自然科学基金2项、重庆市自然科学基金2项、重庆邮电大学基金1项、企业横向项目5项。先后指导研究生30余名，留学生1名。先后在IEEE系列重要期刊和CVPR、AAAi、ACCV、ICMR等重要学术会议上发表学术论文40余篇，其中被SCI收录14篇，CCCV会议最佳论文提名奖1篇，申请发明专利7项，软件著作权7项。部分研究成果已经应用到实际监控场景中。与国内外多所知名高校，包括卡内基梅隆（CMU）、华中科技大学、悉尼科技大学、西安交通大学、哈尔滨工业大学等保持紧密合作关系，已联合培养多名学生。

科研工作 :
主持项目
[1] 国家自然科学基金（面上项目）：复杂监控场景下融合红外和可见光双模信息的小目标事件检测方法研究（**，2016.01-2019.12）[2] 国家自然科学基金（青年基金）：基于高阶张量的红外弱小目标多特性建模与检测方法研究（**，2011.01-2014.12）[3] 重庆市高等学校青年骨干教师资助计划项目：红外弱小目标建模与检测方法研究（2011年）[4] 重庆市科委自然科学基金：复杂背景下基于张量代数的红外微弱目标检测方法研究（CSTC2010BB2411，2010.10-2013.10）[5] 重庆市科委自然科学基金：小目标事件建模与检测方法研究（cstc2014jcyjA40048，2014.07-2016.07）[6] 重庆邮电大学教室智能引导系统建设项目：教室人数智能分析系统 （2015.01-2016.01）[7] ****有限公司（上市公司）：*****智能分析软件运行库（2017.04-2018.04）[8] 重庆邮电大学文峰创新创业项目：复杂场景中事件检测方法研究（WF201404， 2014.7-2016.07）[9] 北京灵昆企业策划有限公司：湖南移动体验厅隔空互动展项开发项目 （2012.05-2014.05）[10] 北京大学数字出版技术国家重点实验室：低质量文档图像中的表格识别方法研究（2012.10-2014.10）
部分期刊论文：
[1] Lan Wang, Chenqiang Gao, Jiang Liu,Deyu Meng, “A novel learning-based frame pooling method for event detection,” Signal Processing, vol. 140, pp. 45-52, 11//, 2017.[2] Chenqiang Gao, Yinhe Du, Jiang Liu, Jing Lv, Luyu Yang, Deyu Meng,Alexander G. Hauptmann, “InfAR dataset: Infrared action recognition at different times,” Neurocomputing, vol. 212, pp. 36-47, 11/5/, 2016.[3] Chenqiang Gao, Pei Li, Yajun Zhang, Jiang Liu,Lan Wang, “People counting based on head detection combining Adaboost and CNN in crowded surveillance environment,” Neurocomputing, vol. 208, pp. 108-116, 10/5/, 2016.[4] Chenqiang Gao, Jun Liu, Qi Feng,Jing Lv, “People-flow counting in complex environments by combining depth and color information,” Multimedia Tools and Applications, vol. 75, no. 15, pp. 9315–9331, 2016.[5] Yan Yan, Feiping Nie, Wen Li, Chenqiang Gao, Yi Yang, Dong Xu, “Image Classification by Cross-Media Active Learning With Privileged Information,” Ieee Transactions on Multimedia, vol. 18, no. 12, pp. 2494-2502, Dec, 2016.[6] Wenhe Liu, Chenqiang Gao, Xiaojun Chang, Qun Wu, “Unified discriminating feature analysis for visual category recognition,” Journal of Visual Communication and Image Representation, vol. 40, Part B, pp. 772-778, 10//, 2016.[7] Chenqiang Gao, Luyu Yang, Yinhe Du, Zemin Feng, Jiang Liu, “From constrained to unconstrained datasets: an evaluation of local action descriptors and fusion strategies for interaction recognition, ” World Wide Web Journal, 2015, vol. 10.1007/s11280-015-0348-y, pp. 1-12, 2015/05/02, 2015.[8] Deyu Meng, Biao Zhang, Zongben Xu, Lei Zhang, Chenqiang, Gao. Robust low-rank tensor factorization by cyclic weighted median. Science in China Series F: Information Sciences, vol. 10.1007/s11432-014-5223-4, pp. 1-11, 2014.[9] Qian Zhao, Deyu Meng, Zongben Xu, Chenqiang Gao. A block coordinate descent approach for sparse principal component analysis. Neurocomputing, vol. 2014.11.038, no. 0, 2014. (DOI:10.1137/**[10] Chenqiang Gao, Deyu Meng, Yi Yang, Yongtao Wang, Xiaofang Zhou, Alex Hauptmann. Patch-Image Model for Small Target Detection in a Single Image. IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 4996-5009, 2013.[11] Chenqiang Gao, Tianqi Zhang, Qiang Li. Small infrared target detection using sparse ring representation. IEEE Aerospace and Electronic Systems Magazine, vol. 27, no. 3, pp. 21-30, 2012.[12] Yongtao Wang, Junbin Gong, Dazhi Zhang, Chenqiang Gao, Jinwen Tian, and Huanqiang Zeng . Large Disparity Motion Layer Extraction via Topological Clustering, IEEE Transactions on Image Processing. vol. 20, no. 1, pp. 43-52, 2010.[13] Wang Peng, Tian Jinwen, Gao chenqiang. Infrared small target detection using directional highpass filters based on LS-SVM. Electronics Letters, vol. 45, no. 3, pp. 156-158, 2009.[14] Chenqing Gao, Jinwen Tian,Peng Wang. Generalised-structure-tensor-based infrared small target detection. Electronics Letters, vol. 44, no. 23, pp. 1349-1351, 2008.
部分会议论文：
[1] Jiang Liu, Jia Chen, De Cheng, Chenqiang Gao, Alexander G. Hauptmann, rewind to track: parallelized apprenticeship learning with backward tracklets, ICME 2017.[2] Jiang Liu, Chenqiang Gao, Deyu Meng,Wangmeng Zuo, “Two-Stream Contextualized CNN for Fine-Grained Image Classification,” in Thoirtieth AAAI Conference on Artificial Intelligence, 2016.[3] Zhenzhong Lan, Lu Jiang, Shoou-I Yu, Shourabh Rawat, Yang Cai, Chenqiang Gao, et al. CMU Informedia @TRECVID 2013: Multimedia Event Detection and Recounting(MED and MER). In Proc. TRECVID, 2013. Chenqiang Gao, Yinhe Du, Jiang Liu, Luyu Yang,Deyu Meng, "A New Dataset and Evaluation for Infrared Action Recognition," CCCV 2015. （最佳论文提名奖）[4] Luyu Yang, Chenqiang Gao, Deyu Meng,Lu Jiang, “A Novel Group-sparsity-optimization-based Feature Selection Model for Complex Interaction Recognition,” in Asian Conference on Computer Vision (ACCV), pp. 508-521, 2014 [5] Chenqiang Gao, Deyu Meng, Wei Tong, Yi Yang, Yang Cai, Haoquan Shen, Gaowen Liu, Shicheng Xu, Alexander Hauptmann. Interactive Surveillance Event Detection through Mid-level Discriminative Representation. ACM International Conference on Multimedia Retrieval (ICMR), Glasgow, UK, April 1-4, pp. 305-312, 2014[6] Yi Peng, Deyu Meng, Zongben Xu, Chenqiang Gao, Yi Yang, Biao Zhang. Decomposable Nonlocal Tensor Dictionary Learning for Multispectral Image Denoising. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, June 24-27, pp. 2949-2956, 2014.[7] Chenqiang Gao, Yang Cai, Haoquan Shen, Wei Tong, Yi Yang, Nicolas Ballas, Deyu Meng, Yan Yan, Alex Hauptmann. CMU Informedia @TREVID 2013: Surveillance Event Detection (SED).In Proc. TRECVID, 2013.

教育背景 :
中国地质大学（武汉）工学学士，华中科技大学工学博士，美国卡内基梅隆大学（CMU）博士后