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中文
Xu Chi

Professor
Doctoral Supervisor
Master Tutor


Gender : Male
Alma Mater : 华中科技大学
Education Level : Faculty of Higher Institutions
Degree : Doctoral Degree in Engineering
School/Department : School of Automation
Date of Employment : 2017-09-07
Contact Information : xuchi[at]cug.edu.cn (Please Replace [at] with @)
Click : times

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Personal Profile

主要从事计算机视觉、模式识别、深度学习、深度传感器人手位姿估计、机器人视觉定位与增强现实方面研究工作。研究中发现了视觉测量PnP理论中导致严重稳定性退化的“准奇异状态”并提出有效解决方法,提出了第一个完备的透视三线问题(P3L)解集分类并提供了系统的理论分析,基于Lie群代数理论建立了一般关节物体位姿估计统一框架,提出了一种新颖的人手关节链结构Hough随机森林估计方法,进行了视觉位姿估计交叉学科应用研究,取得了多项研究成果。

在国内外期刊会议上发表论文20余篇,其中2012年以来以第一/通讯作者在计算机视觉与模式识别领域顶级期刊 IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI,影响因子8.329)与顶级期刊 International Journal of Computer Vision (IJCV,影响因子8.222)上发表论文4篇。研究成果应用于航空航天、机械装配、生物试验等领域,取得良好效果,并在计算机视觉顶级会议IEEE International Conference on Computer Vision(ICCV 2013)、新加坡政府公众活动(SSF 2014)等公共场合多次现场演示,反响良好。

研究兴趣包括:计算机视觉,模式识别,深度学习,人手位姿估计,相机位姿估计,康复机器人,家庭服务机器人、视觉定位导航,增强现实,人机交互,机器学习等。


欢迎对以上研究方向感兴趣的同学报考我的硕士 / 博士研究生


电子邮箱:

 

科研项目:

• “融合透视投影几何与深度学习的多关节体三维位姿求解稳定性分析”,主持,国家自然科学基金(面上项目),中国地质大学(武汉)

• “实时深度图像人手位姿估计方法及其稳定性分析”,主持,国家自然科学基金(面上项目),中国地质大学(武汉)

• “中央高校杰出人才培育基金”,主持,中央高校基金,中国地质大学(武汉)

• “卸船机无人值守系统”,主持,横向项目,中国地质大学(武汉)

• “机器视觉在轨道交通装备制造过程的应用”,主持,横向项目,中国地质大学(武汉)

• “基于虚拟个体行为逼近的多机器人自学习决策与协调控制一体化”,参与,国家自然科学基金(面上项目),中国地质大学(武汉)

• “A Real-time Immersive Toolkit for 3D Biological Visualization and Annotation”,技术骨干,A*STAR JCO Grant,新加坡科技局

• “空间机械臂视觉测量系统研究”,技术骨干,上海航天预研项目,华中科技大学。

• “智能装配关键技术研究”,技术骨干,十一五基础科研项目,华中科技大学。

 

学术会议职务:

• IEEE CVPR 2015 Workshop on Observing and understanding hands in action (HANDS 2015)程序委员会主席之一(Program Committee Chair)。


会议现场演示:

• ICCV 2013(计算机视觉顶级会议)现场演示,得到国际专家同行的关注与认同;

• 新加坡政府公众活动“新加坡科技节2014”现场演示,向公众展示最新科技进展;

• A*STAR Scientific Conference 2014最佳现场演示奖。


担任以下知名国际期刊会议的审稿人:

• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

• International Journal of Computer Vision (IJCV)

• IEEE Transactions on Image Processing (TIP) 

• IEEE Transactions on Mobile Computing (TMC)

• IEEE Transactions on Intelligent Transportation Systems (T-ITS)

• IEEE Transactions on Cybernetics (TC)

• Computer Vision and Image Understanding (CVIU)

• Pattern Recognition (PR)

• IEEE Conference on Computer Vision and Pattern (CVPR)

• Association for the Advancement of Artificial Intelligence (AAAI)

European Conference on Computer Vision (ECCV)

• British Machine Vision Conference (BMVC)
 

部分学术论文列表:

[J1]  Chi Xu, Lakshmi Govindarajan, Yu Zhang, Li Cheng (2017), ‘Lie-X: Depth Image Based Articulated Object Pose Estimation, Tracking, and Action Recognition on Lie Groups’, International Journal of Computer Vision (IJCV, IF:8.222), 123(3), 454–478. (SCI索引: 000403559600008)

[J2]  Chi Xu, Lilian Zhang, Li Cheng, Reinhard Koch (2017), ‘Pose Estimation from Line Correspondences: A Complete Analysis and a Series of Solutions’, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI, IF:8.329), 39(6), 1209–1222. (SCI检索:000401091200012)

[J3]  Chi Xu, Ashwin Nanjappa, Xiaowei Zhang, Li Cheng (2015), ‘Estimate Hand Poses Efficiently from Single Depth Images’, International Journal of Computer Vision (IJCV, IF:8.222), 116(1), 21–45. (SCI检索: 000369422500002)

[J4]  Shiqi Li, Chi Xu*, Ming Xie (2012), ‘A Robust O (n) Solution to the Perspective-N-Point Problem’, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI, IF:8.329), 34 (7), 1444–1450. (SCI检索: 000304138300015) 通讯作者

[J5]  Chi Xu, Lakshmi Govindarajan, Li Cheng (2017), ‘Hand action detection from ego-centric depth sequences with error-correcting Hough transform’, Pattern Recognition (PR, IF:4.582). (DOI: 10.1016/j.patcog.2017.08.009)

[J6]  Shiqi Li, Chi Xu* (2011), ‘Efficient lookup table based camera pose estimation for augmented reality’, Computer animation and virtual worlds, 22(1), 47–58. (SCI检索: 000287820600005) 通讯作者

[J7]  Shiqi Li, Chi Xu* (2011), ‘A stable direct solution of perspective-three-point problem’, International journal of pattern recognition and artificial intelligence, 25(05), 627–642. (SCI检索: 000294118300002) 通讯作者

[J8]  C. Ma, A. Wang, G. Chen, Chi Xu (2018). Hand joints-based gesture recognition for noisy dataset using nested interval unscented kalman filter with LSTM network. The Visual Computer, 34(6), 1053-1063. (SCI检索)doi:10.1007/s00371-018-1556-0

[J9]  Xinyu Shao, Bingang Wang, Yunqing Rao, Liang Gao, Chi Xu (2010), ‘Metaheuristic approaches to sequencing mixed-model fabrication/assembly systems with two objectives’, International Journal of Advanced Manufacturing Technology, 48(9), 1159–1171. (SCI检索: 000277795100029)

[J10] Shiqi Li, Tao Peng, Junfeng Wang, Chi Xu (2009), ‘Mixed Reality-Based Interactive Technology for Aircraft Cabin Assembly’, Chinese Journal of Mechanical Engineering, 22(3): 403–409. (SCI检索: 000267310600014)

[J11] Liang Wang, Yisheng Zhang, Bin Zhu, Chi Xu, Xiaowei Tian, Chao Wang, Jianhua Mo, Li Jian (2012), ’GPU accelerated parallel cholesky factorization’, Applied Mechanics and Materials, 1370–1373, (EI检索)

[C1]  Chi Xu, Li Cheng (2013), ‘Efficient hand pose estimation from a single depth image’, in ‘IEEE International Conference on Computer Vision’ (ICCV, 顶级会议, CCF-A类).

[C2]  Lilian Zhang, Chi Xu*, Kokmeng Lee, Reinhard Koch (2012), ‘Robust and efficient pose estimation from line correspondences’, in ‘Asian Conference on Computer Vision’ (ACCV). 通讯作者

[C3]  Chi Xu, Li Cheng (2018), ‘A Flexible Method for Time-of-Flight Camera Calibration Using Random Forest’, in ‘International Conference on Smart Multimedia’ (ICSM).

[C4]  Ashwin Nanjappa, Chi Xu, Li Cheng (2015), ’GHand: A GPU Algorithm for Realtime Hand Pose Estimation Using Depth Camera’, in ‘Eurographics (Posters)’ (EG)

[C5]  Chi Xu, Shiqi Li, Junfeng Wang, Tao Peng, Ming Xie (2008), ‘Occlusion handling in Augmented Reality system for human-assisted assembly task’, in ‘International Conference on Intelligent Robotics and Applications’


软件著作权与专利:

基于增强现实的装配训练系统软件V1.0(计算机软件著作权登记号:2008SR26895)

信息增强的舱体内结构智能装配系统软件V1.0(计算机软件著作权登记号:2008SR26898)

用于细长腔体的视觉检测装置(发明专利号:ZL 2008 1 0048014.5)

Other Contact Information

Research Focus

  • Computer Vision, Hand Pose Estimation, Camera Pose Estimation, Robotics, Augmented Reality, Machine Learning, etc.