专题中喝计算学食通就第17卷第2期2021年2月 的探索来践行“知行合一”，拓展感知范畴，通过 谢磊 对感知性能的迭代提升来追寻“止于至善”，探索 CCF高级会员。南京大学计算机科学与 感知极限。 技术系教授、博导。教育部青年长江学者。 CCF普适计算专委秘书长。主要研究方 向为普适计算、智能感知计算。 lxie@nju.edu.cn 参考文献 王楚豫 [1]Wang F.et al.Person-in-WiFi:Fine-grained person perception CCF专业会员。南京大学计算机科学与 using WiFi[Cll/Proceedings of the IEEE International 技术系助理研究员。CCF普适计算专委 Conference on Computer Vision,2019:5452-61. 委员。主要研究方向为RFID无源感知 [2]Zheng Y,et al.Zero-effort cross-domain gesture 计算。 chuyu@nju.edu.cn recognition with Wi-Fi[Clll Proceedings of the 17th Annual International Conference on Mobile Systems, Applications.and Services,2019:313-25. 卜艳玲 [3]Wang J,et al.RF-IDraw:virtual touch screen in the CCF学生会员。南京大学计算机科学 与技术系博士研究生。主要研究方向为 air using RF signals[J].ACM S/GCOMM Computer RFD无源感知计算。 Communication Review,2014,44(4):235-46. yanling @smail.nju.edu.cn [4]Bu Y.et al.RF-3DScan:RFID-based 3D Reconstruction on Tagged Packages[J].IEEE Transactions on Mobile Computing,2019 其他作者：宁静仪陆桑璐 [5]Bu Y,et al.RF-Dial:An RFID-based 2D human-computer interaction via tag array [Cl/IEEE INFOCOM 2018-IEEE [12]Xie L.et al.TaggedAR:An RFID-based Approach for Conference on Computer Communications,2018:837-45 Recognition of Multiple Tagged Objects in Augmented [6]Wang C,et al.RF-kinect:A wearable RFID-based Reality Systems.IEEE Transactions on Mobile approach towards 3D body movement tracking[C]// Computing,2018,18(5y1188-202 Proceedings of the ACM on Interactive,Mobile,Wearable [13]An Z,et al.Cross-frequency communication:Near- and Ubiquitous Technologies,2018,2(1):1-28 field identification of uhf rfids with wifi!Proceedings [7]Wang C,et al.Spin-Antenna:3d motion tracking for of the 24th Annual International Conference on Mobile tag array labeled objects via spinning antenna[Cl// Computing and Networking,2018:623-38 IEEE INFOCOM 2019-IEEE Conference on Computer [14]Liu J,et al.Tag-compass:Determining the spatial direction Communications.2019:1-9 of an object with small dimensions.IEEE INFOCOM [8]Gong Y,et al.RF-brush:3D human-computer interaction 2017-IEEE Conference on Computer Communications, via linear tag array.2018 IEEE 15th International 2017:1-9 Conference on Mobile Ad Hoc and Sensor Systems [15]Yu Y,et al.RFID based real-time recognition of ongoing (MASS),2018:290-8 gesture with adversarial learning.Proceedings of the 17th [9]Yang L,et al.Tagoram:Real-time tracking of mobile RFID Conference on Embedded Networked Sensor Systems, tags to high precision using COTS devices.Proceedings 2019:298-310 of the 20th annual interational conference on Mobile [16]Fan X,et al.When RFID meets deep learning:Exploring computing and networking,2014:237-48 cognitive intelligence for activity identification.IEEE [1O]Liu X,et al.Accurate Localization of Tagged Objects Wireless Communications.2019.26(3):19-25 Using Mobile RFID-augmented Robots.IEEE [17]Xie L,et al.Multi-touch in the air:Concurrent Transactions on Mobile Computing.2019 micromovement recognition using RF signals.IEEE/ [11]Shangguan L,et al.Relative Localization of (RFID] ACM Transactions on Networking.2017,26(1):231-44 Tags using Spatial-Temporal Phase Profiling.12th [18]Han J,et al.Butterfly:Environment-Independent physical- (USENIX]Symposium on Networked Systems Design layer authentication for passive RFID.Proceedings of the and Implementation ((NSDI)15).2015:251-63 ACM on Interactive,Mobile,Wearable and Ubiquitous 2626 专题 第 17 卷  第 2 期  2021 年 2 月 参考文献 [1] Wang F, et al. Person-in-WiFi: Fine-grained person perception using WiFi[C]// Proceedings of the IEEE International Conference on Computer Vision, 2019: 5452-61. [2] Zheng Y, et al. Zero-effort cross-domain gesture recognition with Wi-Fi[C]// Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services, 2019: 313-25. [3] Wang J, et al. RF-IDraw: virtual touch screen in the air using RF signals[J]. ACM SIGCOMM Computer Communication Review, 2014, 44(4): 235-46. [4] Bu Y, et al. RF-3DScan: RFID-based 3D Reconstruction on Tagged Packages[J]. IEEE Transactions on Mobile Computing, 2019 [5] Bu Y, et al. RF-Dial: An RFID-based 2D human-computer interaction via tag array[C]// IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 2018: 837-45 [6] Wang C, et al. RF-kinect: A wearable RFID-based approach towards 3D body movement tracking[C]// Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018, 2(1): 1-28 [7] Wang C, et al. Spin-Antenna: 3d motion tracking for tag array labeled objects via spinning antenna[C]// IEEE INFOCOM 2019-IEEE Conference on Computer Communications, 2019: 1-9 [8] Gong Y, et al. RF-brush: 3D human-computer interaction via linear tag array. 2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), 2018: 290-8 [9] Yang L, et al. Tagoram: Real-time tracking of mobile RFID tags to high precision using COTS devices. Proceedings of the 20th annual international conference on Mobile computing and networking, 2014: 237-48 [10] Liu X, et al. Accurate Localization of Tagged Objects Using Mobile RFID-augmented Robots. IEEE Transactions on Mobile Computing, 2019 [11] Shangguan L, et al. Relative Localization of {RFID} Tags using Spatial-Temporal Phase Profiling. 12th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 15), 2015: 251-63 谢  磊 CCF 高级会员。南京大学计算机科学与 技术系教授、博导。教育部青年长江学者。 CCF 普适计算专委秘书长。主要研究方 向为普适计算、智能感知计算。 lxie@nju.edu.cn 王楚豫 CCF 专业会员。南京大学计算机科学与 技术系助理研究员。CCF 普适计算专委 委员。主要研究方向为 RFID 无源感知 计算。 chuyu@nju.edu.cn 卜艳玲 CCF 学生会员。南京大学计算机科学 与技术系博士研究生。主要研究方向为 RFID 无源感知计算。 yanling@smail.nju.edu.cn 其他作者：宁静仪  陆桑璐 更多参考文献：http://dl.ccf.org.cn/cccf/list 的探索来践行“知行合一”，拓展感知范畴，通过 对感知性能的迭代提升来追寻“止于至善”，探索 感知极限。 ■ [12] Xie L, et al. TaggedAR: An RFID-based Approach for Recognition of Multiple Tagged Objects in Augmented Reality Systems. IEEE Transactions on Mobile Computing, 2018, 18(5): 1188-202 [13] An Z, et al. Cross-frequency communication: Near￾field identification of uhf rfids with wifi! Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, 2018: 623-38 [14] Liu J, et al. Tag-compass: Determining the spatial direction of an object with small dimensions. IEEE INFOCOM 2017-IEEE Conference on Computer Communications, 2017: 1-9 [15] Yu Y, et al. RFID based real-time recognition of ongoing gesture with adversarial learning. Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 2019: 298-310 [16] Fan X, et al. When RFID meets deep learning: Exploring cognitive intelligence for activity identification. IEEE Wireless Communications, 2019, 26(3): 19-25 [17] Xie L, et al. Multi-touch in the air: Concurrent micromovement recognition using RF signals. IEEE/ ACM Transactions on Networking, 2017, 26(1): 231-44 [18] Han J, et al. Butterfly: Environment-Independent physical￾layer authentication for passive RFID. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous