The TUM Gait from Audio, Image and Depth (GAID) database: Multimodal recognition of subjects and traits

Histograms of Oriented Gradients for Human Detection

Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584 · see citing works

The WEKA data mining software: an update

Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750 · see citing works

Adaptive background mixture models for real-time tracking

Stauffer, C., & Grimson, W. E. L. (2003) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.1999.784637 · Cited by 6,925 · see citing works

The random subspace method for constructing decision forests

Ho, T. K. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.709601 · Cited by 6,874 · see citing works

Region Filling and Object Removal by Exemplar-Based Image Inpainting

Criminisi, A., Perez, P., & Toyama, K. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2004.833105 · Cited by 3,258 · cited 1× · see citing works

Opensmile: the munich versatile and fast open-source audio feature extractor

Eyben, F., Wöllmer, M., & Schuller, B. (2010) · Proceedings of the 18th ACM international conference on Multimedia · doi:10.1145/1873951.1874246 · Cited by 2,642 · see citing works

Individual recognition using gait energy image

Han, J., & Bhanu, B. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.38 · Cited by 1,873 · see citing works

General Tensor Discriminant Analysis and Gabor Features for Gait Recognition

Tao, D., Li, X., Wu, X., & Maybank, S. J. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1096 · Cited by 1,140 · see citing works

The humanID gait challenge problem: data sets, performance, and analysis

Sarkar, S., Phillips, P. J., Liu, Z., Vega, I. R., Grother, P., & Bowyer, K. W. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.39 · Cited by 1,133 · see citing works

A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition

Yu, S., Tan, D., & Tan, T. (2006) · 18th International Conference on Pattern Recognition (ICPR'06) · doi:10.1109/icpr.2006.67 · Cited by 1,056 · see citing works

Identification of Humans Using Gait

Kale, A. A., Sundaresan, A., Rajagopalan, A. N., Cuntoor, N. P., Roy–Chowdhury, A. K., Krüger, V., & Chellappa, R. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2004.832865 · Cited by 569 · see citing works

Untitled work

(2001) · Cited by 555 · see citing works

Silhouette-based human identification from body shape and gait

Collins, R. T., Gross, R., & Shi, J. (2003) · doi:10.1109/afgr.2002.1004181 · Cited by 504 · see citing works

Recognizing People by Their Gait : The Shape of Motion

Little, J. J. (1998) · Cited by 455 · see citing works

Automated person recognition by walking and running via model-based approaches

Yam, C.-Y., Nixon, M. S., & Carter, J. N. (2004) · Pattern Recognition · doi:10.1016/j.patcog.2003.09.012 · Cited by 354 · see citing works

Improved gait recognition by gait dynamics normalization

Liu, Z., & Sarkar, S. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.122 · Cited by 340 · see citing works

Stride and cadence as a biometric in automatic person identification and verification

BenAbdelkader, C., Davis, L., & Cutler, R. (2002) · Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition · doi:10.1109/afgr.2002.1004182 · Cited by 289 · see citing works

AVEC 2011–The First International Audio/Visual Emotion Challenge

Schuller, B. W., Valstar, M., Eyben, F., McKeown, G. J., Cowie, R., & Pantić, M. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24571-8_53 · Cited by 270 · see citing works

The OU-ISIR Gait Database Comprising the Treadmill Dataset

Makihara, Y., Mannami, H., Tsuji, A., Hossain, M. A., Sugiura, K., Mori, A., & Yagi, Y. (2012) · IPSJ Transactions on Computer Vision and Applications · doi:10.2197/ipsjtcva.4.53 · Cited by 237 · see citing works

Integrated face and gait recognition from multiple views

Shakhnarovich, G., Lee, L., & Darrell, T. J. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2001.990508 · Cited by 218 · see citing works

A Multi-view Method for Gait Recognition Using Static Body Parameters

Johnson, A. Y., & Bobick, A. (2001) · Lecture notes in computer science · doi:10.1007/3-540-45344-x_44 · Cited by 192 · see citing works

A hidden Markov model based framework for recognition of humans from gait sequences

Sundaresan, A., RoyChowdhury, A., & Chellappa, R. (2004) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2003.1246624 · Cited by 170 · see citing works

Efficient spatio-temporal hole filling strategy for Kinect depth maps

Camplani, M., & Salgado, L. (2012) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.911909 · Cited by 162 · see citing works

Gait energy volumes and frontal gait recognition using depth images

Sivapalan, S., Chen, D., Denman, S., Sridharan, S., & Fookes, C. (2011) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/ijcb.2011.6117504 · Cited by 152 · see citing works

Fusion of gait and face for human identification

Kale, A. A., Roy–Chowdhury, A. K., & Chellappa, R. (2004) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2004.1327257 · Cited by 107 · see citing works

The Effect of Time on Gait Recognition Performance

Matovski, D. S., Nixon, M. S., Mahmoodi, S., & Carter, J. N. (2011) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2011.2176118 · Cited by 104 · see citing works

The University of Southampton Multi-Biometric Tunnel and introducing a novel 3D gait dataset

Seely, R. D., Samangooei, S., Lee, M., Carter, J. N., & Nixon, M. S. (2008) · IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) · doi:10.1109/btas.2008.4699353 · Cited by 98 · see citing works

Feature fusion of side face and gait for video-based human identification

Zhou, X., & Bhanu, B. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2007.06.019 · Cited by 94 · see citing works

Combining multiple evidences for gait recognition

Cuntoor, N. P., Kale, A. A., & Chellappa, R. (2003) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2003.1221261 · Cited by 90 · see citing works

2.5D gait biometrics using the Depth Gradient Histogram Energy Image

Hofmann, M. R., Bachmann, S., & Rigoll, G. (2012) · IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) · doi:10.1109/btas.2012.6374606 · Cited by 79 · see citing works

Gait-based age estimation using a whole-generation gait database

Makihara, Y., Okumura, M., Iwama, H., & Yagi, Y. (2011) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/ijcb.2011.6117531 · Cited by 78 · see citing works

Feature Fusion of Face and Gait for Human Recognition at a Distance in Video

Zhou, X., & Bhanu, B. (2006) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2006.556 · Cited by 75 · see citing works

Multimodal biometrics using geometry preserving projections

Zhang, T., Li, X., Tao, D., & Yang, J. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2007.06.035 · Cited by 68 · see citing works

Acoustic Doppler sonar for gait recogination

Kalgaonkar, K., & Raj, B. (2007) · IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) · doi:10.1109/avss.2007.4425281 · Cited by 58 · see citing works

Gait Recognition in the Presence of Occlusion: A New Dataset and Baseline Algorithms

Hofmann, M. R., Sural, S., & Rigoll, G. (2011) · Digital Library (University of West Bohemia) · Cited by 57 · see citing works

Face and Human Gait Recognition Using Image-to-Class Distance

Huang, Y., Xu, D., & Cham, T. (2009) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2009.2035852 · Cited by 56 · see citing works

Combined face and gait recognition using alpha matte preprocessing

Hofmann, M. R., Schmidt, S. M., Rajagopalan, A. N., & Rigoll, G. (2012) · International Conference on Biometrics · doi:10.1109/icb.2012.6199782 · Cited by 50 · see citing works

Personal identification using footstep detection

Shoji, Y., Takasuka, T., & Yasukawa, H. (2005) · International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) · doi:10.1109/ispacs.2004.1439012 · Cited by 49 · see citing works

A framework for activity-specific human identification

Kale, A. A., Cuntoor, N. P., & Chellappa, R. (2002) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2002.5745449 · Cited by 49 · see citing works

Improved Gait Recognition using Gradient Histogram Energy Image

Hofmann, M. R., & Rigoll, G. (2012) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2012.6467128 · Cited by 40 · see citing works

The User Identification System Using Walking Pattern over the ubiFloor

Yun, J., Lee, S., Woo, W., & Ryu, J. (2003) · 제어로봇시스템학회 국제학술대회 논문집 · Cited by 40 · see citing works

Combining multiple evidences for gait recognition

Cuntoor, N. P., Kale, A. A., & Chellappa, R. (2003) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2003.1199100 · Cited by 38 · see citing works

Identification system for smart homes using footstep sounds

de Carvalho, R. L., & Rosa, P. F. F. (2010) · IEEE International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie.2010.5637551 · Cited by 31 · see citing works

THE USE OF WALKING SOUNDS IN SUPPORTING AWARENESS

Mäkelä, K., Hakulinen, J., & Turunen, M. (2003) · SMARTech Repository (Georgia Institute of Technology) · Cited by 26 · see citing works

Footstep classification using simple speech recognition technique

Itai, A., & Yasukawa, H. (2008) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2008.4542147 · Cited by 26 · see citing works

Footstep Recognition with Psyco-acoustics Parameter

Itai, A., & Yasukawa, H. (2006) · IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) · doi:10.1109/apccas.2006.342254 · Cited by 20 · see citing works

Fusion of Chaotic Measure Into a New Hybrid Face-Gait System for Human Recognition

Lee, T. K. M., Ranganath, S., & Sanei, S. (2006) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2006.591 · Cited by 11 · see citing works

GEINet: View-invariant gait recognition using a convolutional neural network

Shiraga, K., Makihara, Y., Muramatsu, D., Echigo, T., & Yagi, Y. (2016) · 2016 International Conference on Biometrics (ICB) · doi:10.1109/icb.2016.7550060 · Cited by 468 · see citing works

Gait Recognition via Disentangled Representation Learning

Zhang, Z., Tran, L., Yin, X. P., Atoum, Y., Liu, X., Wan, J., & Wang, N. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00484 · Cited by 302 · see citing works

A Survey on Gait Recognition

(2019) · ACM Computing Surveys · doi:10.1145/3230633 · Cited by 303 · see citing works

Biometric recognition by gait: A survey of modalities and features

Connor, P. C., & Ross, A. A. (2018) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2018.01.007 · Cited by 272 · see citing works

Vision-Based Gait Recognition: A Survey

Singh, J. P., Jain, S., Arora, S., & Singh, U. P. (2018) · IEEE Access · doi:10.1109/access.2018.2879896 · Cited by 192 · see citing works

A comprehensive survey on gait analysis: History, parameters, approaches, pose estimation, and future work

Sethi, D., Bharti, S., & Prakash, C. (2022) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2022.102314 · Cited by 182 · see citing works

Deep Learning for Monitoring of Human Gait: A Review

Alharthi, A. S., Yunas, S. U., & Ozanyan, K. B. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2928777 · Cited by 175 · see citing works

On Learning Disentangled Representations for Gait Recognition

Zhang, Z., Tran, L., Liu, F., & Liu, X. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.2998790 · Cited by 158 · see citing works

Multi-task learning for gait-based identity recognition and emotion recognition using attention enhanced temporal graph convolutional network

Sheng, W., & Li, X. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.107868 · Cited by 147 · see citing works

GaitNet: An end-to-end network for gait based human identification

Song, C., Huang, Y., Huang, Y., Jia, N., & Wang, L. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.106988 · Cited by 139 · see citing works

A Survey of Human Gait-Based Artificial Intelligence Applications

Harris, E., Khoo, I., & Demircan, E. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.749274 · Cited by 136 · see citing works

Automatic Learning of Gait Signatures for People Identification

Castro, F. M., Marín-Jiménez, M. J., Guil, N., & de la Blanca, N. P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-59147-6_23 · Cited by 124 · see citing works

LidarGait: Benchmarking 3D Gait Recognition with Point Clouds

Shen, C., Fan, C., Wu, W. H., Wang, R., Huang, G. Q., & Yu, S. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00108 · Cited by 120 · see citing works

Person re-identification by unsupervised video matching

Ma, X., Zhu, X., Gong, S., Xie, X., Hu, J., Lam, K., & Zhong, Y. (2016) · Pattern Recognition · doi:10.1016/j.patcog.2016.11.018 · Cited by 117 · see citing works

The Re-identification Challenge

Gong, S., Cristani, M., Loy, C. C., & Hospedales, T. M. (2014) · Advances in computer vision and pattern recognition · doi:10.1007/978-1-4471-6296-4_1 · Cited by 115 · see citing works

Gait Recognition Based on Deep Learning: A Survey

Filipi Gonçalves dos Santos, C., Oliveira, D. D. S., A. Passos, L., Gonçalves Pires, R., Felipe Silva Santos, D., Pascotti Valem, L., P. Moreira, T., Cleison S. Santana, M., Roder, M., Paulo Papa, J., et al. (2023) · ACM Computing Surveys · doi:10.1145/3490235 · Cited by 108 · see citing works

Gait Recognition in the Wild: A Benchmark

(2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01452 · Cited by 104 · see citing works

A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets, and Challenges

Shen, C., Yu, S., Wang, J., Huang, G. Q., & Wang, L. (2024) · IEEE Transactions on Biometrics Behavior and Identity Science · doi:10.1109/tbiom.2024.3486345 · Cited by 112 · see citing works

Normal and pathological gait classification LSTM model

Николаевна, Х. М., Migniot, C., Morozov, A. A., Sushkova, O. S., & Dipandà, A. (2019) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2018.12.007 · Cited by 102 · see citing works

Gait-based Person Re-identification: A Survey

Nambiar, A., Bernardino, A., & Nascimento, J. C. (2020) · ACM Computing Surveys · doi:10.1145/3243043 · Cited by 96 · see citing works

An End-to-End Multi-Task and Fusion CNN for Inertial-Based Gait Recognition

Delgado-Escaño, R., Castro, F. M., Cózar, J. R., Marín-Jiménez, M. J., & Guil, N. (2018) · IEEE Access · doi:10.1109/access.2018.2886899 · Cited by 90 · see citing works

Lidar-Based Gait Analysis and Activity Recognition in a 4D Surveillance System

Benedek, C., Gálai, B., Nagy, B., & Jankó, Z. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2595331 · Cited by 87 · see citing works

Multimodal feature fusion for CNN-based gait recognition: an empirical comparison

Castro, F. M., Marín-Jiménez, M. J., Guil, N., & de la Blanca, N. P. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-04811-z · Cited by 88 · see citing works

Joint Intensity and Spatial Metric Learning for Robust Gait Recognition

Makihara, Y., Suzuki, A., Muramatsu, D., Li, X., & Yagi, Y. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.718 · Cited by 84 · see citing works

GaitGCI: Generative Counterfactual Intervention for Gait Recognition

Dou, H., Zhang, P., Su, W., Yu, Y., Lin, Y., & Li, X. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00540 · Cited by 80 · see citing works

The OU-ISIR Large Population Gait Database with real-life carried object and its performance evaluation

Uddin, M. Z., Ngo, T. T., Makihara, Y., Takemura, N., Li, X., Muramatsu, D., & Yagi, Y. (2018) · IPSJ Transactions on Computer Vision and Applications · doi:10.1186/s41074-018-0041-z · Cited by 77 · see citing works

Gait Recognition: Databases, Representations, and Applications

Makihara, Y., Matovski, D. S., Nixon, M. S., Carter, J. N., & Yagi, Y. (2015) · Wiley Encyclopedia of Electrical and Electronics Engineering · doi:10.1002/047134608x.w8261 · Cited by 77 · see citing works

Fusion of spatial-temporal and kinematic features for gait recognition with deterministic learning

Deng, M., Wang, C., Cheng, F., & Zeng, W. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.02.014 · Cited by 75 · see citing works

View-invariant gait recognition based on kinect skeleton feature

Sun, J., Wang, Y., Li, J., Wan, W., Cheng, D., & Zhang, H. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-5722-1 · Cited by 75 · see citing works

Multi-modal Gait Recognition via Effective Spatial-Temporal Feature Fusion

Cui, Y., & Kang, Y. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01721 · Cited by 75 · see citing works

Silhouette-based gait recognition via deterministic learning

Zeng, W., Wang, C., & Yang, F. (2014) · Pattern Recognition · doi:10.1016/j.patcog.2014.04.014 · Cited by 71 · see citing works

Deep multi-task learning for gait-based biometrics

Marín-Jiménez, M. J., Castro, F. M., Guil, N., de la Torre, F. N., & Medina-Carnicer, R. (2017) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2017.8296252 · Cited by 70 · see citing works

Evaluation of different feature sets for gait recognition using skeletal data from Kinect

Dikovski, B., Madjarov, G., & Gjorgjevikj, D. (2014) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.1109/mipro.2014.6859769 · Cited by 70 · see citing works

Joint Intensity Transformer Network for Gait Recognition Robust Against Clothing and Carrying Status

Li, X., Makihara, Y., Xu, C., Yagi, Y., & Ren, M. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2912577 · Cited by 69 · see citing works

Pose‐based deep gait recognition

Sokolova, A., & Konushin, A. (2018) · IET Biometrics · doi:10.1049/iet-bmt.2018.5046 · Cited by 69 · see citing works

CASIA-E: A Large Comprehensive Dataset for Gait Recognition

Song, C., Huang, Y., Wang, W., & Wang, L. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3183288 · Cited by 62 · see citing works

Human Body Pose Estimation for Gait Identification: A Comprehensive Survey of Datasets and Models

Topham, L., Khan, W., Al‐Jumeily, D., & Hussain, A. J. (2022) · ACM Computing Surveys · doi:10.1145/3533384 · Cited by 61 · see citing works

Acoustic Gaits: Gait Analysis With Footstep Sounds

Altaf, M. U. B., Butko, T., & Juang, B.-H. F. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2410142 · Cited by 59 · see citing works

Calibrated and synchronized multi-view video and motion capture dataset for evaluation of gait recognition

Kwolek, B., Michalczuk, A., Krzeszowski, T., Świtoński, A., Josiński, H., & Wojciechowski, K. W. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-07945-y · Cited by 58 · see citing works

A Survey of Behavioral Biometric Gait Recognition: Current Success and Future Perspectives

Singh, J. P., Jain, S., Arora, S., & Singh, U. P. (2019) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-019-09375-3 · Cited by 55 · see citing works

Gait recognition and micro-expression recognition based on maximum margin projection with tensor representation

Ben, X., Zhang, P., Yan, R., Yang, M., & Ge, G. (2015) · Neural Computing and Applications · doi:10.1007/s00521-015-2031-8 · Cited by 55 · see citing works

Gait recognition based on 3D skeleton joints captured by kinect

Wang, Y., Sun, J., Li, J., & Zhao, D. (2016) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2016.7532940 · Cited by 53 · see citing works

Acoustic Gait-based Person Identification using Hidden Markov Models

Geiger, J. T., Kneißl, M., Schuller, B. W., & Rigoll, G. (2014) · doi:10.1145/2668024.2668027 · Cited by 50 · see citing works

Fisher Motion Descriptor for Multiview Gait Recognition

Castro, F. M., Marín-Jiménez, M. J., Guil, N., & Muñoz‐Salinas, R. (2016) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s021800141756002x · Cited by 49 · see citing works

Deep Learning Approaches for Human Gait Recognition: A Review

Narayan, V., Awasthi, S., Fatima, N., Faiz, M., & Srivastava, S. (2023) · International Conference on Artificial Intelligence and Smart Communication (AISC) · doi:10.1109/aisc56616.2023.10085665 · Cited by 48 · see citing works

Dynamic Distance-Based Shape Features for Gait Recognition

Whytock, T. P., Belyaev, A. G., & Robertson, N. M. (2014) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-014-0501-8 · Cited by 48 · see citing works

Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-identification

Karianakis, N., Liu, Z., Chen, Y., & Soatto, S. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01228-1_44 · Cited by 48 · see citing works

GAIT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORKS

Sokolova, A. D., & Konushin, A. (2017) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xlii-2-w4-207-2017 · Cited by 46 · see citing works

Evaluation of Cnn Architectures for Gait Recognition Based on Optical Flow Maps

Castro, F. M., Marín-Jiménez, M. J., Guil, N., López-Tapia, S., & de la Blanca, N. P. (2017) · International Conference of the Biometrics Special Interest Group (BIOSIG) · doi:10.23919/biosig.2017.8053503 · Cited by 45 · see citing works

Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods

Parashar, A., Shekhawat, R. S., Ding, W., & Rida, I. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.07.002 · Cited by 43 · see citing works

Siamese denoising autoencoders for joints trajectories reconstruction and robust gait recognition

Sheng, W., & Li, X. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.01.098 · Cited by 42 · see citing works

UGaitNet: Multimodal Gait Recognition With Missing Input Modalities

Marín-Jiménez, M. J., Castro, F. M., Delgado-Escaño, R., Kalogeiton, V. S., & Guil, N. (2021) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2021.3132579 · Cited by 41 · see citing works

Deep Learning-Based Multimodal Abnormal Gait Classification Using a 3D Skeleton and Plantar Foot Pressure

Jun, K., Lee, S., Lee, D.-W., & Kim, M. S. (2021) · IEEE Access · doi:10.1109/access.2021.3131613 · Cited by 39 · see citing works

A Multi-Stage Adaptive Feature Fusion Neural Network for Multimodal Gait Recognition

Zou, S., Xiong, J., Fan, C., Shen, C., Yu, S., & Tang, J. (2024) · IEEE Transactions on Biometrics Behavior and Identity Science · doi:10.1109/tbiom.2024.3384704 · Cited by 37 · see citing works

Multimodal features fusion for gait, gender and shoes recognition

Castro, F. M., Marín-Jiménez, M. J., & Guil, N. (2016) · Machine Vision and Applications · doi:10.1007/s00138-016-0767-5 · Cited by 37 · see citing works

A unified perspective of classification-based loss and distance-based loss for cross-view gait recognition

Han, F., Li, X., Zhao, J., & Shen, F. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2021.108519 · Cited by 37 · see citing works

Multiview gait-based gender classification through pose-based voting

Isaac, E. R. H. P., Elias, S., Rajagopalan, S., & Easwarakumar, K. S. (2018) · Pattern Recognition Letters · doi:10.1016/j.patrec.2018.04.020 · Cited by 35 · see citing works

Evaluation of Algorithms for Orientation Invariant Inertial Gait Matching

Subramanian, R., & Sarkar, S. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2018.2850032 · Cited by 35 · see citing works

Human Gait Analysis: A Sequential Framework of Lightweight Deep Learning and Improved Moth-Flame Optimization Algorithm

Khan, M. A., Arshad, H., Damaševičius, R., Alqahtani, A., Alsubai, S., Binbusayyis, A., Nam, Y., & Kang, B.-G. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/8238375 · Cited by 33 · see citing works

Feature selection for Lidar-based gait recognition

Gálai, B., & Benedek, C. (2015) · International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM) · doi:10.1109/iwcim.2015.7347076 · Cited by 30 · see citing works

Real-time full-body human gender recognition in (RGB)-D data

Linder, T., Wehner, S., & Arras, K. O. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7139616 · Cited by 30 · see citing works

2.5D Multi-View Gait Recognition Based on Point Cloud Registration

Tang, J., Luo, J., Tjahjadi, T., & Gao, Y. (2014) · Sensors · doi:10.3390/s140406124 · Cited by 29 · see citing works

Gait collector: An automatic gait data collection system in conjunction with an experience-based long-run exhibition

Makihara, Y., Kimura, T., Okura, F., Mitsugami, I., Niwa, M., Aoki, C., Suzuki, A., Muramatsu, D., & Yagi, Y. (2016) · International Conference on Biometrics · doi:10.1109/icb.2016.7550090 · Cited by 27 · see citing works

Advancements in artificial intelligence for biometrics: A deep dive into model-based gait recognition techniques

Parashar, A., Parashar, A., Shabaz, M., Gupta, D., Sahu, A. K., & Khan, M. A. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.107712 · Cited by 27 · see citing works

Cross-Covariate Gait Recognition: A Benchmark

Zou, S., Fan, C., Xiong, J., Shen, C., Yu, S., & Tang, J. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i7.28621 · Cited by 27 · see citing works

Recognizing activities of the elderly using wearable sensors: a comparison of ensemble algorithms based on boosting

Wu, Y., Qi, S., Hu, F., Ma, S., Mao, W., & Li, W. (2019) · Sensor Review · doi:10.1108/sr-11-2018-0309 · Cited by 25 · see citing works

Emerging trends in gait recognition based on deep learning: a survey

Munusamy, V., & Senthilkumar, S. S. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2158 · Cited by 24 · see citing works

Gait recognition in the presence of co-variate conditions

Gupta, S. K., & Chattopadhyay, P. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.04.113 · Cited by 24 · see citing works

A diverse and multi-modal gait dataset of indoor and outdoor walks acquired using multiple cameras and sensors

Topham, L., Khan, W., Al‐Jumeily, D., Waraich, A., & Hussain, A. J. (2023) · Scientific Data · doi:10.1038/s41597-023-02161-8 · Cited by 24 · see citing works

Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video Dataset

Ranjan, R., Ahmedt‐Aristizabal, D., Armin, M. A., & Kim, J. (2025) · IEEE Access · doi:10.1109/access.2025.3545787 · Cited by 23 · see citing works

You Can Run but not Hide: Improving Gait Recognition with Intrinsic Occlusion Type Awareness

Gupta, A., & Chellappa, R. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00579 · Cited by 23 · see citing works

ReSGait: The Real-Scene Gait Dataset

Mu, Z., Castro, F. M., Marín-Jiménez, M. J., Guil, N., Li, Y.-R., & Yu, S. (2021) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/ijcb52358.2021.9484347 · Cited by 21 · see citing works

A multi-modal dataset for gait recognition under occlusion

Li, N., & Zhao, X. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03474-8 · Cited by 21 · see citing works

Learning Gait Representations with Noisy Multi-Task Learning

Cosma, A., & Radoi, E. (2022) · Italian National Conference on Sensors · doi:10.3390/s22186803 · Cited by 26 · see citing works

Gait Recognition With Drones: A Benchmark

Li, A., Hou, S., Cai, Q., Fu, Y., & Huang, Y. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3312931 · Cited by 21 · see citing works

Gait Recognition in Large-scale Free Environment via Single LiDAR

Han, X., Ren, Y., Cong, P., Sun, Y., Wang, J., Xu, L., & Ma, Y. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681166 · Cited by 21 · see citing works

Exploiting gradient histograms for gait-based person identification

Hofmann, M. R., & Rigoll, G. (2013) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2013.6738859 · Cited by 21 · see citing works

Gait Recognition Under Different Clothing Conditions Via Deterministic Learning

Deng, M., & Wang, C. (2024) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2018.7511096 · Cited by 21 · see citing works

The Toronto older adults gait archive: video and 3D inertial motion capture data of older adults’ walking

Mehdizadeh, S., Nabavi, H., Sabo, A., Arora, T., Iaboni, A., & Taati, B. (2022) · Scientific Data · doi:10.1038/s41597-022-01495-z · Cited by 21 · see citing works

A survey of appearance-based approaches for human gait recognition: techniques, challenges, and future directions

Şahan, P. G., Şahın, S., & Gülağız, F. K. (2024) · The Journal of Supercomputing · doi:10.1007/s11227-024-06172-z · Cited by 20 · see citing works

Simple and efficient pose-based gait recognition method for challenging environments

de Lima, V. C., de Melo, V. H. C., & Schwartz, W. R. (2020) · Pattern Analysis and Applications · doi:10.1007/s10044-020-00935-z · Cited by 20 · see citing works

Artificial Intelligence and Pro-Social Behaviour

Bryson, J. J. (2015) · Springer eBooks · doi:10.1007/978-3-319-15515-9_15 · Cited by 21 · see citing works

Learning Age From Gait: A Survey

Aderinola, T. B., Connie, T., Ong, T. S., Yau, W., & Teoh, A. B. J. (2021) · IEEE Access · doi:10.1109/access.2021.3095477 · Cited by 19 · see citing works

Color-mapped contour gait image for cross-view gait recognition using deep convolutional neural network

Linda, G. M., Themozhi, G., & Bandi, S. R. (2019) · International Journal of Wavelets Multiresolution and Information Processing · doi:10.1142/s0219691319410121 · Cited by 19 · see citing works

Gait recognition using partial silhouette-based approach

Shaikh, S. H., Saeed, K., & Chaki, N. (2014) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin.2014.6776930 · Cited by 19 · see citing works

Energy‐based tuning of convolutional neural networks on multi‐GPUs

Castro, F. M., Guil, N., Marín-Jiménez, M. J., Pérez-Serrano, J., & Ujaldón, M. (2018) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.4786 · Cited by 20 · see citing works

Person re-identification in indoor videos by information fusion using Graph Convolutional Networks

Soni, K., Dogra, D. P., Sekh, A. A., Kar, S., Choi, H., & Kim, I.-J. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118363 · Cited by 18 · see citing works

AFPILD: Acoustic footstep dataset collected using one microphone array and LiDAR sensor for person identification and localization

Wu, S., Huang, S., Liu, Z., Zhang, Q., & Liu, J. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.102181 · Cited by 17 · see citing works

Occluded Gait Recognition with Mixture of Experts: An Action Detection Perspective

Huang, P., Peng, Y., Hou, S., Cao, C., Liu, X., He, Z., & Huang, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72658-3_22 · Cited by 17 · see citing works

Gait Recognition in the Wild: A Large-Scale Benchmark and NAS-Based Baseline

Guo, X., Zhu, Z. D., Yang, T., Lin, B., Huang, J., Deng, J., Huang, G., Zhou, J., & Lu, J. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3546482 · Cited by 17 · see citing works

Combining gait and face for tackling the elapsed time challenges

Yu, G., Wei, X., Li, C., Marcialis, G. L., Roli, F., & Massimo Tistarelli, A. (2013) · IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) · doi:10.1109/btas.2013.6712749 · Cited by 17 · see citing works

Gait-Based Age Estimation Using a DenseNet

Sakata, A., Makihara, Y., Takemura, N., Muramatsu, D., & Yagi, Y. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21074-8_5 · Cited by 17 · see citing works

Enhancing gait recognition by multimodal fusion of mobilenetv1 and xception features via PCA for OaA-SVM classification

Pundir, A., Sharma, M., Pundir, A., Saini, D., Ouahada, K., Bharany, S., Rehman, A. U., & Hamam, H. (2024) · Scientific Reports · doi:10.1038/s41598-024-68053-y · Cited by 16 · see citing works

On covariate factor detection and removal for robust gait recognition

Whytock, T. P., Belyaev, A. G., & Robertson, N. M. (2015) · Machine Vision and Applications · doi:10.1007/s00138-015-0681-2 · Cited by 16 · see citing works

Extending Appearance Based Gait Recognition with Depth Data

Lenac, K., Sušanj, D., Ramakić, A., & Pinčić, D. (2019) · Applied Sciences · doi:10.3390/app9245529 · Cited by 16 · see citing works

A novel biometric recognition method based on multi kernelled bijection octal pattern using gait sound

Aydemir, E., Tuncer, T., Doğan, Ş., & Unsal, M. (2020) · Applied Acoustics · doi:10.1016/j.apacoust.2020.107701 · Cited by 16 · see citing works

Gait-based person identification by spectral, cepstral and energy-related audio features

Geiger, J. T., Hofmann, M. R., Schuller, B. W., & Rigoll, G. (2013) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2013.6637689 · Cited by 16 · see citing works

Recognition of a Person Wearing Sport Shoes or High Heels through Gait Using Two Types of Sensors

Derlatka, M., & Bogdan, M. (2018) · Sensors · doi:10.3390/s18051639 · Cited by 16 · see citing works

A Review of Techniques on Gait-Based Person Re-Identification

Rahi, B. H., Li, M., & Qi, M. (2023) · International Journal of Network Dynamics and Intelligence · doi:10.53941/ijndi0201005 · Cited by 15 · see citing works

On how to improve tracklet-based gait recognition systems

Marín-Jiménez, M. J., Castro, F. M., Carmona-Poyato, A., & Guil, N. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2015.08.025 · Cited by 15 · see citing works

Multimodal features fusion for gait, gender and shoes recognition

Castro, F. M., Marín-Jiménez, M. J., & Guil, N. (2016) · Machine Vision and Applications · doi:10.1007/s00138-016-0767-5 · Cited by 37 · see citing works

Empirical Study of Audio-Visual Features Fusion for Gait Recognition

Castro, F. M., Marín-Jiménez, M. J., & Guil, N. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-23192-1_61 · Cited by 7 · see citing works

MMGait: Benchmarking and Unifying Gait Recognition across Heterogeneous ModalitiesPreprint

Hou, S., Wang, C., Cai, Q., Li, A., & Huang, Y. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2609.11601

Human Recognition under Multi-Gait Scenario

Singh, J. (. M. D. (n.d.) · Data Archiving and Networked Services (DANS) · doi:10.17632/py4zw6g7xc.1

Multimodal Biometric Database for Person Identification and Gait Analysis

Chetty, G. (2015) · International Conference on Intelligent Information Processing · Cited by 1 · see citing works