Journal of Guangdong University of Technology ›› 2022, Vol. 39 ›› Issue (03): 83-88.doi: 10.12052/gdutxb.210082
Previous Articles Next Articles
Zhang Zi-ran1, Song Wen-fang1, Zhang Zu-yao2
CLC Number:
[1] 钟贤权. 当代皮影艺术的生存困境与现代创新[J]. 中华文化论坛, 2013(5): 131-135. ZHONG X Q. The survival dilemma and modern innovation of contemporary shadow puppets art [J]. Journal of Chinese Culture, 2013(5): 131-135. [2] 辛雨璇, 邹墨馨. 皮影艺术的数字化保护与传承思路探索[J]. 戏剧之家, 2020(23): 48-50. XIN Y X, ZOU M X. Exploring the idea of digital preservation and inheritance of shadow puppets art [J]. Home Drama, 2020(23): 48-50. [3] 高星, 苏宇伦, 王泽宇. 华县皮影面临失传困境[J]. 人民周刊, 2018(12): 90-91. GAO X, SU Y L, WANG Z Y. Huaxian shadow puppets faces the dilemma of loss [J]. People's Weekly, 2018(12): 90-91. [4] 张海超. 影随展动寓教于乐——巡展中的唐山皮影表演[J]. 文物鉴定与鉴赏, 2019(4): 133. ZHANG H C. Shadow moves with the exhibition educating and entertaining—Tangshan shadow performance in the touring exhibition[J] Identification and Appreciation to Cultural Relics, 2019(4): 133. [5] 赵双柱, 包亚飞, 潘思凡, 等. 基于AR技术的非遗文化的保护与开发研究——以甘肃环县道情皮影戏为例[J]. 兰州文理学院学报(自然科学版), 2017, 31(6): 89-92. ZHAO S Z, BAO Y F, PAN S F, et al. On the protection and development of intangible cultural heritage by using AR—a case study of Daoqing shadow play in Huan county, Gansu [J]. Journal of Lanzhou University of Arts and Science (Natural Sciences), 2017, 31(6): 89-92. [6] 刘虹弦. 江汉平原皮影戏艺术特征及数字化研究[J]. 武汉纺织大学学报, 2020, 33(5): 3-7. LIU H X. Research on the artistic characteristics and digitalization of shadow play in Jianghan plain [J]. Journal of Wuhan Textile University, 2020, 33(5): 3-7. [7] 洪诗莹. 网络传播视域下的山东泰山皮影手机应用设计研究[D]. 济南: 山东大学, 2019. [8] TIAN Y Z, WANG G P, LI L, et al. A universal self-adaption workspace mapping method for human-robot interaction using Kinect sensor data [J]. IEEE Sensors Journal, 2020, 20(14): 7918-7928. [9] LIU F L, ZENG W, YUAN C Z, et al. Kinect-based hand gesture recognition using trajectory information, hand motion dynamics and neural networks [J]. Artificial Intelligence Review, 2019, 52(1): 563-583. [10] ASHWINI K, AMUTHA R. Compressive sensing-based recognition of human upper limb motions with Kinect skeletal data [J]. Multimedia Tools and Applications, 2021, 80: 1-19. [11] 曾碧, 林展鹏, 邓杰航. 自主移动机器人走廊识别算法研究与改进[J]. 广东工业大学学报, 2015, 33(5): 9-14. ZENG B, LIN Z P, DENG J H. Algorithm research on recognition and improvement for corridor of autonomous mobile robot [J]. Journal of Guangdong University of Technology, 2015, 33(5): 9-14. [12] 高金潇, 陈亦楠, 李福浩. 基于Kinect的动作识别跟踪的机械臂平台[J]. 科技资讯, 2019, 17(15): 1-4. GAO J X, CHEN Y N, LI F H. Kinect-based robotic arm platform for motion recognition tracking [J]. Science & Technology Information, 2019, 17(15): 1-4. [13] 徐军, 孟月霞, 王天伦, 等. 基于Kinect的仿人机器人控制系统[J]. 传感器与微系统, 2017, 36(9): 97-100. XU J, MENG Y X, WANG T L, et al. Control system for humanoid robot based on Kinect [J]. Transducer and Microsystem Technologies, 2017, 36(9): 97-100. [14] 胡敦利, 柯浩然, 张维. 基于Kinect和ROS的骨骼轨迹人体姿态识别研究[J]. 高技术通讯, 2020, 30(2): 177-184. HU D L, KE H R, ZHANG W. Research on human body attitude recognition based on Kinect and ROS [J]. Chinese High Technology Letters, 2020, 30(2): 177-184. [15] 吴智敏, 何汉武, 吴悦明. 基于混合现实交互的指挥棒位姿跟踪[J]. 广东工业大学学报, 2018, 35(3): 107-112. WU Z M, HE H W, WU Y M. Baton-like attitude tracking based on mixed reality interaction [J]. Journal of Guangdong University of Technology, 2018, 35(3): 107-112. [16] 王刚, 孙太任, 丁胜培. 动态受限机械臂的局部加权学习控制[J]. 系统仿真学报, 2019, 31(4): 733-739. WANG G, SUN T R, DING S P. Locally weighted learning control for dynamic restricted manipulators [J]. Journal of System Simulation, 2019, 31(4): 733-739. [17] 李琪, 王向东, 李华. 基于双Kinect传感器的三维人体姿态跟踪方法[J]. 系统仿真学报, 2020, 32(8): 1446-1454. LI Q, WANG X D, LI H. 3D human pose tracking approach based on double Kinect sensors [J]. Journal of System Simulation, 2020, 32(8): 1446-1454. [18] HUANG X F, SUN S Q, ZHANG K J, et al. A method of shadow puppet figure modeling and animation [J]. Frontiers of Information Technology & Electronic Engineering, 2015, 5: 367-379. [19] SHU J, HAMANO F, ANQUS J. Application of extended Kalman filter for improving the accuracy and smoothness of Kinect skeleton-joint estimates [J]. Journal of Engineering Mathematics, 2014, 88: 161-175. [20] CHIN L, EU K S, TAY T T, et al. A posture recognition model dedicated for differentiating between proper and improper sitting posture with Kinect sensor[C]// 2019 IEEE International Symposium on Haptic, Audio and Visual Environments and Games (HAVE). Subang Jaya: IEEE, 2019: 1-5. [21] LI P. Research on robot boxing movement simulation based on Kinect sensor [J]. EURASIP Journal on Wireless Communications and Networking, 2020, 147(1): 2-15. |
[1] | ZENG Bi, LIN Zhan-peng, DENG Jie-hang. Algorithm Research on Recognition and Improvement for Corridor of Autonomous Mobile Robot [J]. Journal of Guangdong University of Technology, 2016, 33(05): 9-14. |
|