[en] Driver’s behavior and gesture recognition are most significant in the emerging next-generation vehicular technology. Driver’s face
may provide important cues about his/her attention and fatigue behavior. Therefore, driver’s face pose is one of the key indicators
to be considered for automatic driver monitoring system in next-generation Internet of Vehicles (IoV) technology. Driver
behavior monitoring is most significant in order to reduce road accidents. This paper aims to address the problem of driver’s
attentiveness monitoring using face pose estimation in a nonintrusive manner. The proposed system is based on wireless
sensing, leveraging channel state information (CSI) of WiFi signals. In this paper, we present a novel classification algorithm
that is based on the combination of support vector machine (SVM) and K nearest neighbor (KNN) to enhance the
classification accuracy. Experimental results demonstrate that the proposed device-free wireless implementation can localize a
driver’s face very accurately with an average recognition rate of 91:8%.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Akhtar, Zain ul Abidin
Rassol, Hafiz Faiz
Asif, Muhammad
KHAN, Wali Ullah ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Jaffri, Zain ul Abidin
External co-authors :
yes
Language :
English
Title :
Driver’s Face Pose Estimation Using Fine-Grained Wi-Fi Signals for Next-Generation Internet of Vehicles
Alternative titles :
[en] Driver’s Face Pose Estimation Using Fine-Grained Wi-Fi Signals for Next-Generation Internet of Vehicles
Publication date :
05 May 2022
Journal title :
Wireless Communications and Mobile Computing
ISSN :
1530-8669
eISSN :
1530-8677
Publisher :
John Wiley & Sons, Hoboken, United States - New Jersey
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Bibliography
Khan W. U., Li X., Ihsan A., Khan M. A., Menon V. G., Ahmed M., NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks under Imperfect SIC Decoding 2021, IEEE Transactions on Intelligent Transportation Systems 10.1109/TITS.2021.3091402
Khan W. U., Nguyen T. N., Jameel F., Jamshed M. A., Pervaiz H., Javed M. A., Jantti R., Learning-Based Resource Allocation for Backscatter-Aided Vehicular Networks 2021, IEEE Transactions on Intelligent Transportation Systems 10.1109/TITS.2021.3126766
Khan W. U., Javed M. A., Nguyen T. N., Khan S., Elhalawany B. M., Elhalawany B. M., Energy-Efficient Resource Allocation for 6G Backscatter-Enabled NOMA IoV Networks 2021, IEEE Transactions on Intelligent Transportation Systems 10.1109/TITS.2021.3110942
Khan W. U., Jameel F., Kumar N., Jäntti R., Guizani M., Backscatter-enabled efficient V2X communication with non-orthogonal multiple access. IEEE Transactions on Vehicular Technology 2021, 70, 2, 1724, 1735, 10.1109/TVT.2021.3056220
Dahmane A., Larabi S., Bilasco I. M., Djeraba C., Head pose estimation based on face symmetry analysis. Signal, Image and Video Processing 2015, 9, 8, 1871, 1880, 10.1007/s11760-014-0676-x, 2-s2.0-84942296613
Diaz-Chito K., Hernández-Sabaté A., López A. M., MLópez A., A reduced feature set for driver head pose estimation. Applied Soft Computing 2016, 45, 98, 107, 10.1016/j.asoc.2016.04.027, 2-s2.0-84966701576
WKithil P., Jones R. D., McCuish J., Driver alertness detection research using capacitive sensor array. Technical report, SAE Technical Paper 2001
Patel M., Lal S. K. L., Kavanagh D., Rossiter P., Lal S. K. L., Kavanagh D., Rossiter P., Applying neural network analysis on heart rate variability data to assess driver fatigue. Expert Systems with Applications 2011, 38, 6, 7235, 7242, 10.1016/j.eswa.2010.12.028, 2-s2.0-79951579523
Martin S., Ohn-Bar E., Tawari A., Trivedi M. M., Understanding head and hand activities and coordination in naturalistic driving videos. In 2014 IEEE Intelligent Vehicles Symposium Proceedings 2014, IEEE
Tran C., Doshi A., Trivedi M. M., Modeling and prediction of driver behavior by foot gesture analysis. Computer Vision and Image Understanding 2012, 116, 3, 435, 445, 10.1016/j.cviu.2011.09.008, 2-s2.0-84856095760
Vicente F., Huang Z., Xiong X., de la Torre F., Zhang W., Levi D., Driver gaze tracking and eyes off the road detection system. IEEE Transactions on Intelligent Transportation Systems 2015, 16, 4, 2014, 2027, 10.1109/TITS.2015.2396031, 2-s2.0-85027940377
Jo H., Lee M., In-attention state monitoring for a driver based on head pose and eye blinking detection using one class support vector machine. In International Conference on Neural Information Processing 2014, Springer 110, 117
He Y., Chen Y., Hu Y., Zeng B., WiFi vision: sensing, recognition, and detection with commodity MIMO-OFDM WiFi. IEEE Internet of Things Journal 2020, 7, 9, 8296, 8317, 10.1109/JIOT.2020.2989426
Fei H., Xiao F., Han J., Huang H., Sun L., Multi-variations activity based gaits recognition using commodity WiFi. IEEE Transactions on Vehicular Technology 2020, 69, 2, 2263, 2273, 10.1109/TVT.2019.2962803
Wang F., Gong W., Liu J., Kui W., Channel selective activity recognition with wifi: a deep learning approach exploring wideband information. IEEE Transactions on Network Science and Engineering 2020, 7, 1, 181, 192, 10.1109/TNSE.2018.2825144, 2-s2.0-85045307568
Zhang J., Wu F., Wei B., Zhang Q., Huang H., Shah S. W., Cheng J., Data augmentation and dense-LSTM for human activity recognition using WiFi signal. IEEE Internet of Things Journal 2021, 8, 6, 4628, 4641, 10.1109/JIOT.2020.3026732
Venkatnarayan R. H., Mahmood S., Shahzad M., WiFi based multi-user gesture recognition. IEEE Transactions on Mobile Computing 2021, 20, 3, 1242, 1256, 10.1109/TMC.2019.2954891
Guo Z., Xiao F., Sheng B., Fei H., Shui Y., WiReader: adaptive air handwriting recognition based on commercial WiFi signal. IEEE Internet of Things Journal 2020, 7, 10, 10483, 10494, 10.1109/JIOT.2020.2997053
Yan H., Zhang Y., Wang Y., Kangle X., WiAct: a passive WiFi-based human activity recognition system. IEEE Sensors Journal 2020, 20, 1, 296, 305, 10.1109/JSEN.2019.2938245
Yang X., Cao R., Zhou M., Xie L., Temporal-frequency attention-based human activity recognition using commercial WiFi devices. IEEE Access 2020, 8, 137758, 137769, 10.1109/ACCESS.2020.3012021
Zuo J., Zhu X., Peng Y., Zhao Z., Wei X., Wang X., A new method of posture recognition based on WiFi signal. IEEE Communications Letters 2021, 25, 8, 2564, 2568, 10.1109/LCOMM.2021.3081135
Xiao C., Lei Y., Ma Y., Zhou F., Qin Z., DeepSeg: deep-learning-based activity segmentation framework for activity recognition using WiFi. IEEE Internet of Things Journal 2021, 8, 7, 5669, 5681, 10.1109/JIOT.2020.3033173
Ding J., Wang Y., Xiangcong F., Wihi: WiFi based human identity identification using deep learning. IEEE Access 2020, 8, 129246, 129262, 10.1109/ACCESS.2020.3009123
Ma X., Zhao Y., Liang Z., Practical device-free gesture recognition using WiFi signals based on metalearning. IEEE Transactions on Industrial Informatics 2020, 16, 1, 228, 237, 10.1109/TII.2019.2909877
Shen X., Ni Z., Liu L., Yang J., Ahmed K., WiPass: 1D-CNN-based smartphone keystroke recognition using WiFi signals. Pervasive and Mobile Computing 2021, 73, 101393
Li F., Valero M., Shahriar H., Khan R. A., Ahamed S. I., Wi-COVID: a COVID-19 symptom detection and patient monitoring framework using WiFi. Smart Health 2021, 19, 100147
Ahmed H. F. T., Ahmad H., Narasingamurthi K., Harkat H., Phang S. K., DF-WiSLR: device-free Wi-Fi-based sign language recognition. Pervasive and Mobile Computing 2020, 69, 101289
Asif M., Zhou W., Ajmal M., Akhtar Z. u. A., Khan N. A., A construction of high performance quasicyclic LDPC codes: a combinatoric design approach. Wireless Communications and Mobile Computing, vol. 2019, 2019, 1, 10, 10.1155/2019/7468792, 2-s2.0-85062320792
Asif M., Zhou W., Yu Q., Li X., Khan N. A., A deterministic construction for jointly designed quasicyclic LDPC coded-relay cooperation. Wireless Communications and Mobile Computing 2019, 2019
Asif M., Zhou W., Yu Q., Jointly designed quasi-cyclic LDPC-coded cooperation with diversity combining at receiver. International Journal of Distributed Sensor Networks 2020, 16, 7
Asif M., Khan W. U., Afzal H. M., Reduced-complexity LDPC decoding for next-generation IoT networks. Wireless Communications and Mobile Computing, vol. 2021, 2021
Wang Y., Jiang X., Cao R., Wang X., Robust indoor human activity recognition using wireless signals. Sensors 2015, 15, 7, 17195, 17208, 10.3390/s150717195, 2-s2.0-84940186614, 26184231
Wang T., Yang D., Zhang S., Wu Y., Shugong X., Wi-Alarm: low-cost passive intrusion detection using WiFi. Sensors 2019, 19, 10, 2335
Ali K., Liu A. X., Wang W., Shahzad M., Recognizing keystrokes using WiFi devices. IEEE Journal on Selected Areas in Communications 2017, 35, 5, 1175, 1190, 10.1109/JSAC.2017.2680998, 2-s2.0-85019712339
Wang Y., Wu K., Ni L. M., Ni L. M., WiFall: device-free fall detection by wireless networks. IEEE Transactions on Mobile Computing 2017, 16, 2, 581, 594, 10.1109/TMC.2016.2557792, 2-s2.0-85009813246
Peng H., Jia W., WiFind: driver fatigue detection with fine-grained Wi-Fi signal features. IEEE Transactions on Big Data (Early Access) 2018, 1, 1
Yongliang X., Limin X., Shot boundary detection based on supervised locality preserving projections and KNN-SVM classifier. In 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics 2010, IEEE 11262926
Halperin D., Hu W., Sheth A., Wetherall D., Tool release. ACM SIGCOMM Computer Communication Review 2011, 41, 1, 53, 53, 10.1145/1925861.1925870, 2-s2.0-79551483702
Liu M., Zhang L., Yang P., Lu L., Gong L., Wi-Run: device-free step estimation system with commodity Wi-Fi. Journal of Network and Computer Applications 2019, 143, 77, 88, 10.1016/j.jnca.2019.05.004, 2-s2.0-85067887784
Li F., Alqaness M. A. A., Zhang Y., Zhao B., Luan X., A robust and device-free system for the recognition and classification of elderly activities. Sensors 2043, 16, 12, 2016
Dong Z., Li F., Ying J., Pahlavan K., Indoor motion detection using Wi-Fi channel state information in flat floor environments versus in staircase environments. Sensors 2018, 18, 7, 2177
Xu Y., Xiong F., Shao Y., Niu Q., WmFall: WiFi-based multistage fall detection with channel state information. International Journal of Distributed Sensor Networks 2018, 14, 10
Lv J., Man D., Wu Y., Robust device-free intrusion detection using physical layer information of WiFi signals. Applied Sciences 2019, 19, 1, 175
Ding E., Li X., Zhao T., Zhang L., Yanjun H., A robust passive intrusion detection system with commodity WiFi devices. Journal of Sensors, page 2018, 2018, 1, 12, 10.1155/2018/8243905, 2-s2.0-85055689490
Al-qaness M. A. A., Device-free human micro-activity recognition method using WiFi signals. Geo-spatial Information Science 2019, 22, 2, 128, 137, 10.1080/10095020.2019.1612600, 2-s2.0-85065794457
Zhang L., Gao Q., Ma X., Wang J., Yang T., Wang H., DeFi: robust training-free device-free wireless localization with WiFi. IEEE Transactions on Vehicular Technology 2018, 67, 9, 8822, 8831, 10.1109/TVT.2018.2850842, 2-s2.0-85049139938
Al-qaness M. A. A., Li F., WiGer: WiFi-based gesture recognition system. International Journal of Geo-Information 2016, 5, 6, 92
Zhangjie F., Xu J., Zhu Z., Liu A. X., Sun X., Writing in the air with WiFi signals for virtual reality devices. IEEE Transactions on Mobile Computing 2019, 18, 2, 473, 484, 10.1109/TMC.2018.2831709, 2-s2.0-85046470726
Tian Z., Wang J., Yang X., Zhou M., WiCatch: a Wi-Fi based hand gesture recognition system. IEEE Access 2018, 6, 16911, 16923, 10.1109/ACCESS.2018.2814575, 2-s2.0-85043457093
Akhtar Z. U. A., Wang H., WiFibased driver's activity monitoring with efficient computation of radio-image features. Sensors 2020, 20, 5, 1381
Akhtar Z. U. A., Wang H., WiFibased gesture recognition for vehicular infotainment system-an integrated approach. Applied Sciences 2019, 9, 24, 5268
Akhtar Z. U. A., Wang H., WiFi-based driver's activity recognition using multi-layer classification. Neurocomputing 2020, 405, 12, 25, 10.1016/j.neucom.2020.04.133
Duan S., Yu T., He J., WiDriver: driver activity recognition system based on WiFi CSI. International Journal of Wireless Information Networks 2018, 25, 2, 146, 156, 10.1007/s10776-018-0389-0, 2-s2.0-85042454105
Ma Y., Zhou G., Wang S., Zhao H., Jung W., SignFi. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018, 2, 1, 1, 21, 10.1145/3191755
Wang W., Liu A. X., Shahzad M., Ling K., Sanglu L., Device-free human activity recognition using commercial WiFi devices. IEEE Journal on Selected Areas in Communications 2017, 35, 5, 1118, 1131, 10.1109/JSAC.2017.2679658, 2-s2.0-85019732077
Kholoud M., Norjihan G., Abdul H. S., Babar R. M., Human activity classification using decision tree and Naïve Bayes classifiers. Multimedia Tools and Applications 2020, 80, 21709, 21726
Kanokoda T., Kushitani Y., Shimada M., Shirakashi J.-i., Gesture prediction using wearable sensing systems with neural networks for temporal data analysis. Sensors 2019, 19, 3, 710
Goswami P., Rao S., Bharadwaj S., Nguyen A., Real-time multi-gesture recognition using 77 GHz FMCW MIMO single chip radar. In 2019 IEEE International Conference on Consumer Electronics (ICCE) 2019, IEEE 1, 4
Zhang T., Song T., Chen D., Zhang T., Zhuang J., WiGrus: a WiFi-based gesture recognition system using software-defined radio. IEEE Access 2019, 7, 131102, 131113, 10.1109/ACCESS.2019.2940386
Tan B., Chen Q., Chetty K., Woodbridge K., Li W., Piechocki R., Exploiting WiFi channel state information for residential healthcare informatics. IEEE Communications Magazine 2018, 56, 5, 130, 137, 10.1109/MCOM.2018.1700064, 2-s2.0-85047341549
Al-qaness M. A. A., Li F., Ma X., Zhang Y., Guo L., Devicefree indoor activity recognition system. Applied Sciences 2016, 6, 11, 329
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