17.1.3.6.22 Human Action Recognition, Indoor Environments, Classroom, Smart Room

Chapter Contents (Back)
Activity Recognition. Action Recognition. Human Actions. Human Motion. Smart Room. Indoor Environment. Classroom Environment.
See also Human Action Recognition, Office, Meetings.
See also Human Activities, Interacting with Objects. Instructional videos:
See also Instructional, Training Videos, How To, Teach Machine How.

Tao, J.[Ji], Tan, Y.P.[Yap-Peng],
A probabilistic approach to incorporating domain knowledge for closed-room people monitoring,
SP:IC(19), No. 10, December 2004, pp. 959-974.
Elsevier DOI 0501
BibRef
Earlier:
People monitoring using face recognition with observation constraints,
ICIP04(III: 1437-1440).
IEEE DOI 0505
BibRef

Peursum, P.[Patrick], Bui, H.H.[Hung H.], Venkatesh, S.[Svetha], West, G.A.W.[Geoff A.W.],
Robust Recognition and Segmentation of Human Actions Using HMMs with Missing Observations,
JASP(2005), No. 13, 2005, pp. 2110-2126.
WWW Link. 0603
BibRef
Earlier:
Human action segmentation via controlled use of missing data in HMMs,
ICPR04(IV: 440-445).
IEEE DOI 0409
BibRef

Peursum, P.[Patrick], Venkatesh, S.[Svetha], West, G.A.W.[Geoff A.W.],
A Study on Smoothing for Particle-Filtered 3D Human Body Tracking,
IJCV(87), No. 1-2, March 2010, pp. xx-yy.
Springer DOI 1001
BibRef
Earlier:
Tracking-as-Recognition for Articulated Full-Body Human Motion Analysis,
CVPR07(1-8).
IEEE DOI 0706
BibRef
Earlier:
Observation-Switching Linear Dynamic Systems for Tracking Humans Through Unexpected Partial Occlusions by Scene Objects,
ICPR06(IV: 929-934).
IEEE DOI 0609
BibRef
Earlier: A1, A3, A2:
Combining Image Regions and Human Activity for Indirect Object Recognition in Indoor Wide-Angle Views,
ICCV05(I: 82-89).
IEEE DOI 0510
BibRef

Lu, Y.[Yao], Li, L.[Ling], Peursum, P.,
Background Suppression for Building Accurate Appearance Models in Human Motion Tracking,
DICTA12(1-6).
IEEE DOI 1303
BibRef

Truyen, T.T.[Tran The], Phung, D.Q.[Dinh Q.], Venkatesh, S.[Svetha], Bui, H.H.[Hung H.],
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition,
CVPR06(II: 1686-1693).
IEEE DOI 0606
BibRef

McKenna, S.J.[Stephen J.], Nait-Charif, H.[Hammadi],
Tracking human motion using auxiliary particle filters and iterated likelihood weighting,
IVC(25), No. 6, 1 June 2007, pp. 852-862.
Elsevier DOI 0704
BibRef
Earlier:
Learning spatial context from tracking using penalised likelihoods,
ICPR04(IV: 138-141).
IEEE DOI 0409
Human tracking; Particle filters; Iterated likelihood weighting; Supportive environments; Head tracking BibRef

Ward, J.A., Lukowicz, P.[Paul], Troster, G.[Gerhard], Starner, T.E.,
Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers,
PAMI(28), No. 10, October 2006, pp. 1553-1567.
IEEE DOI 0609
Tracking hand and sound to provide feedback to assembly and maintenance workers. BibRef

Zhou, Z., Chen, X., Chung, Y.C., He, Z.H., Han, T.X., Keller, J.M.,
Activity Analysis, Summarization, and Visualization for Indoor Human Activity Monitoring,
CirSysVideo(18), No. 11, November 2008, pp. 1489-1498.
IEEE DOI 0811
BibRef

Hsu, W.L., Hsiao, C.C., Chang, Y.L., Chen, T.L.,
Vision-based monitoring method using gray relational analysis,
IET-CV(3), No. 3, September 2009, pp. 103-111.
DOI Link 0909
Room surveillance using cellular model. BibRef

Guethmundsson, S.A.[Sigurjon Arni], Pardas, M.[Montse], Casas, J.R.[Josep R.], Sveinsson, J.R.[Johannes R.], Aanaes, H.[Henrik], Larsen, R.[Rasmus],
Improved 3D reconstruction in smart-room environments using ToF imaging,
CVIU(114), No. 12, December 2010, pp. 1376-1384.
Elsevier DOI 1011
Time-of-Flight; 3D reconstruction; Background modeling; Shape-from-Silhouette; Sensor fusion BibRef

Guomundsson, S.A.[Sigurjon Arni], Larsen, R.[Rasmus], Aanaes, H.[Henrik], Pardas, M.[Montse], Casas, J.R.[Josep Ramon],
ToF imaging in Smart room environments towards improved people tracking,
TOF-CV08(1-6).
IEEE DOI 0806
BibRef

Kosmopoulos, D.I.[Dimitrios I.], Doulamis, N.D.[Nikolaos D.], Voulodimos, A.S.[Athanasios S.],
Bayesian filter based behavior recognition in workflows allowing for user feedback,
CVIU(116), No. 3, March 2012, pp. 422-434.
Elsevier DOI 1201
Bayesian filter; Hidden Markov models; Behavior recognition; Workflow; User feedback BibRef

Voulodimos, A.S.[Athanasios S.], Doulamis, A.D.[Anastasios D.], Kosmopoulos, D.I.[Dimitrios I.], Varvarigou, T.A.[Theodora A.],
Video summarization guiding evaluative rectification for industrial activity recognition,
ARTEMIS11(950-957).
IEEE DOI 1201
BibRef
Earlier: A2, A1, A3, A4:
Enhanced human behavior recognition using HMM and evaluative rectification,
ARTEMIS10(39-44).
DOI Link 1111
BibRef

Kosmopoulos, D.I.[Dimitrios I.], Voulodimos, A.S.[Athanasios S.], Varvarigou, T.A.[Theodora A.],
Robust Human Behavior Modeling from Multiple Cameras,
ICPR10(3575-3578).
IEEE DOI 1008
BibRef

Cook, D.J.[Diane J.],
Learning Setting-Generalized Activity Models for Smart Spaces,
IEEE_Int_Sys(27), No. 1, January-February 2012, pp. 32-38.
IEEE DOI 1203
BibRef

Wu, C.L., Fu, L.C.,
Design and Realization of a Framework for Human-System Interaction in Smart Homes,
SMC-A(42), No. 1, January 2012, pp. 15-31.
IEEE DOI 1112
BibRef

Hazarika, S.M.[Shyamanta M.], Bhowmick, A.[Alexy],
Learning rules of a card game from video,
AIR(38), No. 1, June 2012, pp. 55-65.
WWW Link. 1208
BibRef

Voulodimos, A.S.[Athanasios S.], Kosmopoulos, D.I.[Dimitrios I.], Vasileiou, G.[Georgios], Sardis, E.[Emmanuel], Anagnostopoulos, V.[Vasileios], Lalos, C.[Constantinos], Doulamis, A.[Anastasios], Varvarigou, T.A.[Theodora A.],
A Threefold Dataset for Activity and Workflow Recognition in Complex Industrial Environments,
MultMedMag(19), No. 3, 2012, pp. 42-52.
IEEE DOI 1209
BibRef
Earlier: A1, A2, A3, A4, A7, A5, A6, A8:
A dataset for workflow recognition in industrial scenes,
ICIP11(3249-3252).
IEEE DOI 1201
BibRef

Alameda-Pineda, X.[Xavier], Staiano, J.[Jacopo], Subramanian, R.[Ramanathan], Batrinca, L., Ricci, E., Lepri, B.[Bruno], Lanz, O., Sebe, N.[Nicu],
SALSA: A Novel Dataset for Multimodal Group Behavior Analysis,
PAMI(38), No. 8, August 2016, pp. 1707-1720.
IEEE DOI 1608
accelerometers BibRef

Krüger, V.[Volker], Herzog, D.L.[Dennis L.],
Tracking in object action space,
CVIU(117), No. 7, July 2013, pp. 764-789.
Elsevier DOI 1305
Action recognition; Parametric gestures; Tracking; Pose estimation BibRef

Herzog, D.L., Krüger, V.[Volker], Grest, D.[Daniel],
Parametric Hidden Markov Models for Recognition and Synthesis of Movements,
BMVC08(xx-yy).
PDF File. 0809
BibRef

Raamana, P.R.[Pradeep Reddy], Grest, D.[Daniel], Krueger, V.[Volker],
Human Action Recognition in Table-Top Scenarios: An HMM-Based Analysis to Optimize the Performance,
CAIP07(101-108).
Springer DOI 0708
BibRef

Prest, A.[Alessandro], Schmid, C.[Cordelia], Ferrari, V.[Vittorio],
Weakly Supervised Learning of Interactions between Humans and Objects,
PAMI(34), No. 3, March 2012, pp. 601-614.
IEEE DOI 1201
Initialize from human detector. combine set of part detectors. Determine action object and spatial relation to person. BibRef

Prest, A.[Alessandro], Ferrari, V.[Vittorio], Schmid, C.[Cordelia],
Explicit Modeling of Human-Object Interactions in Realistic Videos,
PAMI(35), No. 4, April 2013, pp. 835-848.
IEEE DOI 1303
Localize and track both object and person. BibRef

Scalmato, A., Sgorbissa, A., Zaccaria, R.,
Describing and Recognizing Patterns of Events in Smart Environments With Description Logic,
Cyber(43), No. 6, 2013, pp. 1882-1897.
IEEE DOI 1312
Cognition BibRef

Arbab-Zavar, B.[Banafshe], Carter, J.N.[John N.], Nixon, M.S.[Mark S.],
On hierarchical modelling of motion for workflow analysis from overhead view,
MVA(25), No. 2, February 2014, pp. 345-359.
WWW Link. 1402
BibRef

Rivet, B., Wang, W., Naqvi, S.M.A.[Syed Moeen Ali], Chambers, J.,
Audiovisual Speech Source Separation: An overview of key methodologies,
SPMag(31), No. 3, May 2014, pp. 125-134.
IEEE DOI 1405
Audio-visual systems BibRef

Xue, Y.[Yang], Hu, Y.Q.[Yao-Quan], Jin, L.W.[Lian-Wen],
Activity Recognition Based on an Accelerometer in a Smartphone Using an FFT-Based New Feature and Fusion Methods,
IEICE(E97-D), No. 8, August 2014, pp. 2182-2186.
WWW Link. 1408

See also New Rotation Feature for Single Tri-axial Accelerometer Based 3D Spatial Handwritten Digit Recognition, A. BibRef

Lopes, O., Reyes, M., Escalera, S., Gonzalez, J.,
Spherical Blurred Shape Model for 3-D Object and Pose Recognition: Quantitative Analysis and HCI Applications in Smart Environments,
Cyber(44), No. 12, December 2014, pp. 2379-2390.
IEEE DOI 1412
computer graphics BibRef

lo Presti, L.[Liliana], La Cascia, M.[Marco], Sclaroff, S.[Stan], Camps, O.I.[Octavia I.],
Hankelet-based dynamical systems modeling for 3D action recognition,
IVC(44), No. 1, 2015, pp. 29-43.
Elsevier DOI 1601
Hidden Markov Model BibRef

lo Presti, L.[Liliana], La Cascia, M.[Marco],
3D skeleton-based human action classification: A survey,
PR(53), No. 1, 2016, pp. 130-147.
Elsevier DOI 1602
Action recognition BibRef

Benmansour, A.[Asma], Bouchachia, A.[Abdelhamid], Feham, M.[Mohammed],
Multioccupant Activity Recognition in Pervasive Smart Home Environments,
Surveys(48), No. 3, February 2016, pp. Article No 34.
DOI Link 1602
Survey, Smart Home. Human activity recognition in ambient intelligent environments like homes, offices, and classrooms has been the center of a lot of research for many years now. The aim is to recognize the sequence of actions by a specific person using sensor readings BibRef

Woo, D.N.[Daniel N.], Aygün, R.S.[Ramazan S.],
Unsupervised Speaker Identification for TV News,
MultMedMag(23), No. 4, October 2016, pp. 50-58.
IEEE DOI 1612
Character recognition BibRef

Zhao, W., Lun, R., Gordon, C., Fofana, A.B.M., Espy, D.D., Reinthal, M.A., Ekelman, B., Goodman, G.D., Niederriter, J.E., Luo, X.,
A Human-Centered Activity Tracking System: Toward a Healthier Workplace,
HMS(47), No. 3, June 2017, pp. 343-355.
IEEE DOI 1706
Employment, Injuries, Intelligent sensors, Iris recognition, Sensor systems, Alert, Microsoft Kinect, biometrics, gesture recognition, human motion tracking, selective tracking, single sign-on BibRef

Atoum, Y., Chen, L., Liu, A.X., Hsu, S.D.H., Liu, X.,
Automated Online Exam Proctoring,
MultMed(19), No. 7, July 2017, pp. 1609-1624.
IEEE DOI 1706
Feature extraction, Monitoring, Multimedia communication, Sensors, Visualization, Webcams, Covariance feature, gaze estimation, online exam proctoring (OEP), phone detection, speech detection, text detection, user, verification BibRef

Lederman, O., Mohan, A., Calacci, D., Pentland, A.S.,
Rhythm: A Unified Measurement Platform for Human Organizations,
MultMedMag(25), No. 1, January 2018, pp. 26-38.
IEEE DOI 1804
Behavioral sciences, Human factors, Mobile communication, Monitoring, Real-time systems, Social factors, Streaming media, wearable computing BibRef

Nida, N.[Nudrat], Yousaf, M.H.[Muhammad Haroon], Irtaza, A.[Aun], Velastin, S.A.[Sergio A.],
Bag of Deep Features for Instructor Activity Recognition in Lecture Room,
MMMod19(II:481-492).
Springer DOI 1901
BibRef

Kastrati, Z.[Zenun], Imran, A.S.[Ali Shariq], Kurti, A.[Arianit],
Integrating word embeddings and document topics with deep learning in a video classification framework,
PRL(128), 2019, pp. 85-92.
Elsevier DOI 1912
Online course videos. Deep learning, Video classification, Embedding, Document topics, CNN, DNN BibRef

Saini, M.K.[Mukesh Kumar], Goel, N.[Neeraj],
How Smart Are Smart Classrooms? A Review of Smart Classroom Technologies,
Surveys(52), No. 6, December 2019, pp. xx-yy.
DOI Link 2001
Smart, teacher, multimedia, classroom, student, content, assessment BibRef

Hu, H.Y.[Hai-Yang], Cheng, K.M.[Kai-Ming], Li, Z.J.[Zhong-Jin], Chen, J.[Jie], Hu, H.[Hua],
Workflow recognition with structured two-stream convolutional networks,
PRL(130), 2020, pp. 267-274.
Elsevier DOI 2002
Monitoring work. Workflow recognition, Action recognition, Deep learning, Two-stream CNNs BibRef

Liu, Y.[Yang], Kiliç, V.[Volkan], Guan, J.[Jian], Wang, W.W.[Wen-Wu],
Audio-Visual Particle Flow SMC-PHD Filtering for Multi-Speaker Tracking,
MultMed(22), No. 4, April 2020, pp. 934-948.
IEEE DOI 2004
Atmospheric measurements, Particle measurements, Noise measurement, Frequency modulation, Visualization, Optimal Proposal Distribution BibRef

Liu, Y.[Yang], Xu, Y.[Yong], Wu, P.P.[Pei-Pei], Wang, W.W.[Wen-Wu],
Labelled Non-Zero Diffusion Particle Flow SMC-PHD Filtering for Multi-Speaker Tracking,
MultMed(26), 2024, pp. 2544-2559.
IEEE DOI 2402
Visualization, Particle measurements, Atmospheric measurements, Information filters, Target tracking, Filtering algorithms, particle flow BibRef

Nie, Y.[Yong],
On-line classroom visual tracking and quality evaluation by an advanced feature mining technique,
SP:IC(84), 2020, pp. 115817.
Elsevier DOI 2004
Visual tracking, Data mining, Online Classroom, Quality evaluation, Behavior analysis BibRef

Yun, W.H., Lee, D., Park, C., Kim, J., Kim, J.,
Automatic Recognition of Children Engagement from Facial Video Using Convolutional Neural Networks,
AffCom(11), No. 4, October 2020, pp. 696-707.
IEEE DOI 2011
Feature extraction, Face recognition, Cameras, Face, Heuristic algorithms, Machine learning, Databases, pattern recognition BibRef

Beltrán, L.V.B.[L. Viviana Beltrán], Caicedo, J.C.[Juan C.], Journet, N.[Nicholas], Coustaty, M.[Mickaël], Lecellier, F.[François], Doucet, A.[Antoine],
Deep multimodal learning for cross-modal retrieval: One model for all tasks,
PRL(146), 2021, pp. 38-45.
Elsevier DOI 2105
Embeddings, Multimodal learning, Deep learning, Cross-modal, Visual question answering, Evaluation study BibRef

Nguyen, N.V.[Nhu Van], Coustaty, M.[Mickal], Ogier, J.M.[Jean-Marc],
Multi-modal and Cross-Modal for Lecture Videos Retrieval,
ICPR14(2667-2672)
IEEE DOI 1412
Accuracy; Indexing; Semantics; Speech; Videos; Visualization BibRef

Bosch, N.[Nigel], d'Mello, S.K.[Sidney K.],
Automatic Detection of Mind Wandering from Video in the Lab and in the Classroom,
AffCom(12), No. 4, October 2021, pp. 974-988.
IEEE DOI 2112
Physiology, Heart rate, Cameras, Facial features, Support vector machines, Detectors, Human computer interaction, human-computer interaction BibRef

Chen, L.Y.[Li-Yan], Yang, H.R.[Hao-Ran], Liu, K.H.[Kun-Hong],
Classroom Attention Estimation Method Based on Mining Facial Landmarks of Students,
MMMod22(II:255-266).
Springer DOI 2203
BibRef

Islam, M.R.[M. Rabiul], Vargo, A.W.[Andrew W.], Iwata, M.[Motoi], Iwamura, M.[Masakazu], Kise, K.[Koichi],
Exploring Sensor Modalities to Capture User Behaviors for Reading Detection,
IEICE(E105-D), No. 9, September 2022, pp. 1629-1633.
WWW Link. 2209
BibRef

Zhang, F.[Fan],
A novel restricted Boltzmann machine-based temporal-spatial correlation method for student behaviour recognition in depth video,
IJCVR(12), No. 5, 2022, pp. 487-505.
DOI Link 2209
BibRef

Ramakrishnan, A.[Anand], Zylich, B.[Brian], Ottmar, E.[Erin], LoCasale-Crouch, J.[Jennifer], Whitehill, J.[Jacob],
Toward Automated Classroom Observation: Multimodal Machine Learning to Estimate CLASS Positive Climate and Negative Climate,
AffCom(14), No. 1, January 2023, pp. 664-679.
IEEE DOI 2303
Videos, Meteorology, Encoding, Machine learning, Activity recognition, Automatic classroom observation, auditory analysis BibRef

Sümer, Ö.[Ömer], Goldberg, P.[Patricia], D'Mello, S.[Sidney], Gerjets, P.[Peter], Trautwein, U.[Ulrich], Kasneci, E.[Enkelejda],
Multimodal Engagement Analysis From Facial Videos in the Classroom,
AffCom(14), No. 2, April 2023, pp. 1012-1027.
IEEE DOI 2306
Observers, Magnetic heads, Feature extraction, Videos, Psychology, Affective computing, Affective computing, computer vision, nonverbal behaviour understanding BibRef

Xu, Y.P.[Ya-Ping], Li, Y.Y.[Yan-Yan], Chen, Y.[Yunshan], Bao, H.G.[Hao-Gang], Zheng, Y.Q.[Ya-Qian ],
Spontaneous visual database for detecting learning-centered emotions during online learning,
IVC(136), 2023, pp. 104739.
Elsevier DOI 2308
Learning-centered emotions, Emotion recognition, Emotional database, Machine learning, Deep learning BibRef

Li, Y.T.[Ya-Ting], Qi, X.[Xin], Saudagar, A.K.J.[Abdul Khader Jilani], Badshah, A.M.[Abdul Malik], Muhammad, K.[Khan], Liu, S.[Shuai],
Student behavior recognition for interaction detection in the classroom environment,
IVC(136), 2023, pp. 104726.
Elsevier DOI 2308
Surveillance, Relational reasoning, Human-to-object interaction, Action recognition, Intelligent education BibRef

Booth, B.M.[Brandon M.], Bosch, N.[Nigel], D'Mello, S.K.[Sidney K.],
Engagement Detection and Its Applications in Learning: A Tutorial and Selective Review,
PIEEE(111), No. 10, October 2023, pp. 1398-1422.
IEEE DOI 2310
BibRef

Tosato, L.[Lucrezia], Fortier, V.[Victor], Bloch, I.[Isabelle], Pelachaud, C.[Catherine],
Exploiting temporal information to detect conversational groups in videos and predict the next speaker,
PRL(177), 2024, pp. 164-168.
Elsevier DOI 2401
F-formation, Clustering, Temporal information, Next speaker prediction, LSTM BibRef

Banzon, A.M.[Allison Macey], Beever, J.[Jonathan], Taub, M.[Michelle],
Facial Expression Recognition in Classrooms: Ethical Considerations and Proposed Guidelines for Affect Detection in Educational Settings,
AffCom(15), No. 1, January 2024, pp. 93-104.
IEEE DOI 2403
Ethics, Education, Face recognition, Software, Affective computing, Writing, Task analysis, Affective computing, ethical/societal implications BibRef

Wu, D.[Di], Wang, J.[Jun], Zou, W.[Wei], Zou, S.D.[Shao-Dong], Zhou, J.X.[Ju-Xiang], Gan, J.H.[Jian-Hou],
Classroom teacher action recognition based on spatio-temporal dual-branch feature fusion,
CVIU(247), 2024, pp. 104068.
Elsevier DOI 2408
Action recognition, Spatial-temporal feature fusion, Classroom scene, Teacher action BibRef

Abdellaoui, B.[Benyoussef], Remaida, A.[Ahmed], Sabri, Z.[Zineb], Abdellaoui, M.[Mohammed], El Bouzekri-El Idrissi, Y.[Younes], Moumen, A.[Aniss],
Analyzing Recorded Video to Evaluate How Engaged and Emotional Students Are in Remote Learning Environments,
ISCV24(1-7)
IEEE DOI 2408
Emotion recognition, Computer aided instruction, Ethics, Machine learning algorithms, Distance learning, Video sequences, Deep Learning BibRef

Liang, Q.[Qiao], Chen, B.Z.[Bing-Zhi], Gao, Z.X.[Zi-Xian],
Classroom head-up rate detection based on RNN-CNN image recognition algorithm,
CVIDL23(70-74)
IEEE DOI 2403
Adaptation models, Head, Recurrent neural networks, Image recognition, Face recognition, Streaming media, Robustness, Feature extraction BibRef

Rana, R.[Ripon], Dongshik, K.[Kang], Yosiaki, S.[Sasazawa],
Estimation of Student's Interest Reaction Levels in Class Video,
ICCVMI23(1-6)
IEEE DOI 2403
Correlation, Pose estimation, Mouth, Oral communication, Muscles, Data mining, humanpose, openpose, reaction BibRef

Lee, D.W.[Dong Won], Ahuja, C.[Chaitanya], Liang, P.P.[Paul Pu], Natu, S.[Sanika], Morency, L.P.[Louis-Philippe],
Lecture Presentations Multimodal Dataset: Towards Understanding Multimodality in Educational Videos,
ICCV23(20030-20041)
IEEE DOI 2401
BibRef

Dimitriadou, E.A.[Eleni A.], Lanitis, A.[Andreas],
A Systematic Approach for Automated Lecture Style Evaluation Using Biometric Features,
CAIP23(II:3-12).
Springer DOI 2312
BibRef

Singh, S.D.[S. Darshan], Gupta, A.[Anchit], Jawahar, C.V., Tapaswi, M.[Makarand],
Unsupervised Audio-Visual Lecture Segmentation,
WACV23(5221-5230)
IEEE DOI 2302
Visualization, Pandemics, Navigation, Optical character recognition, Motion pictures, Vision + language and/or other modalities BibRef

Li, Y.[Yong], Zhang, S.P.[Shui-Ping],
Character Attentiveness Analysis Based on Deep Learning,
ICRVC22(291-294)
IEEE DOI 2301
Deep learning, Training, Service robots, Fatigue, Feature extraction, Behavioral sciences, target detection, person concentration analysis BibRef

Lee, T.[Taeckyung], Kim, D.[Dain], Park, S.[Sooyoung], Kim, D.[Dongwhi], Lee, S.J.[Sung-Ju],
Predicting Mind-Wandering with Facial Videos in Online Lectures,
CVPM22(2103-2112)
IEEE DOI 2210
Webcams, Computational modeling, Education, Predictive models, Data collection, Physiology BibRef

Yao, P.[Powen], Hou, Y.[Yu], He, Y.[Yuan], Cheng, D.[Da], Hu, H.[Huanpu], Zyda, M.[Michael],
Using Multi-modal Machine Learning for User Behavior Prediction in Simulated Smart Home for Extended Reality,
VAMR22(I:94-112).
Springer DOI 2206
BibRef

Tamaki, R.[Reiya], Nakajima, T.[Tatsuo],
Are You There? A Study on Measuring Presence in Immersive Virtual Reality,
VAMR22(I:275-288).
Springer DOI 2206
BibRef

Copur, O.[Onur], Nakip, M.[Mert], Scardapane, S.[Simone], Slowack, J.[Jürgen],
Engagement Detection with Multi-Task Training in E-Learning Environments,
CIAP22(III:411-422).
Springer DOI 2205
BibRef

Chu, L.[Lutao], Liu, Y.[Yi], Wu, Z.[Zewu], Tang, S.Y.[Shi-Yu], Chen, G.[Guowei], Hao, Y.Y.[Yu-Ying], Peng, J.C.[Jun-Cai], Yu, Z.L.[Zhi-Liang], Chen, Z.[Zeyu], Lai, B.H.[Bao-Hua], Xiong, H.[Haoyi],
PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Dataset,
Activity22(202-209)
IEEE DOI 2202
Teleconferencing, Semantics, Predictive models, Feature extraction, Loss measurement, Real-time systems, Topology BibRef

Guney, C., Akinci, O., Çamoglu, K.,
Artificial Learning-Based Proctoring Solution for Remote Online Assessments: 'VProctor',
SmartCityApp21(235-238).
DOI Link 2201
BibRef

Che, B.L.[Bao-Liang], Li, X.M.[Xiao-Meng], Zhao, Z.L.[Zheng-Li], Lu, W.G.[Wei-Gang], Jiang, P.[Peng],
A Database of Students' Actions Based on Real Classroom Environment,
ICIVC21(76-80)
IEEE DOI 2112
Training, Image resolution, Image recognition, Databases, Benchmark testing, Usability, students' actions, action recognition BibRef

Tran, P.[Phuong], Pattichis, M.[Marios], Celedón-Pattichis, S.[Sylvia], LópezLeiva, C.[Carlos],
Facial Recognition in Collaborative Learning Videos,
CAIP21(II:252-261).
Springer DOI 2112
BibRef

Paliwal, P.[Pinak], Paliwal, V.[Vikas],
3D Scene Angles using UL Decomposition of Planar Homography,
StruCo3D21(2031-2038)
IEEE DOI 2112
Proctoring during online exams. Shape, Surveillance, Image processing, Image edge detection, Software algorithms BibRef

Delgado, K.[Kevin], Origgi, J.M.[Juan Manuel], Hasanpoor, T.[Tania], Yu, H.[Hao], Allessio, D.[Danielle], Arroyo, I.[Ivon], Lee, W.[William], Betke, M.[Margrit], Woolf, B.[Beverly], Bargal, S.A.[Sarah Adel],
Student Engagement Dataset,
ABAW21(3621-3629)
IEEE DOI 2112
Dataset, Classrooms. Training, Deep learning, Visualization, Head, Distance learning, Time series analysis BibRef

Sun, B.[Bo], Wu, Y.[Yong], Hao, Z.[Zhuo], Yan, H.Q.[Huan-Qing], He, J.[Jun],
Student Break Behavior Recognition Dataset,
ICIVC21(72-75)
IEEE DOI 2112
Costs, Education, Manuals, Explosives, Reliability, Artificial intelligence, student break behavior, video dataset, baseline BibRef

Caus, D.[Danu], Carbajal, G.[Guillaume], Gerkmann, T.[Timo], Frintrop, S.[Simone],
See the Silence: Improving Visual-Only Voice Activity Detection by Optical Flow and RGB Fusion,
CVS21(41-51).
Springer DOI 2109
BibRef

Zhang, P.[Peng], Liu, Z.Q.[Zhong-Qi], Chen, X.M.[Xue-Mei], Zhou, Q.X.[Qian-Xiang],
Study on Evaluation Index of Physical Load of Chemical Prevention Personnel in High Temperature and Humidity Environment,
DHM21(I:67-78).
Springer DOI 2108
BibRef

Kota, B.U.[Bhargava Urala], Stone, A.[Alexander], Davila, K.[Kenny], Setlur, S.[Srirangaraj], Govindaraju, V.[Venu],
Automated Whiteboard Lecture Video Summarization by Content Region Detection and Representation,
ICPR21(10704-10711)
IEEE DOI 2105
Measurement, Histograms, Handwriting recognition, Navigation, Feature extraction, Minimization, Videos BibRef

Xu, F.[Fei], Davila, K.[Kenny], Setlur, S.[Srirangaraj], Govindaraju, V.[Venu],
Skeleton-based Methods for Speaker Action Classification on Lecture Videos,
HCAU20(250-264).
Springer DOI 2103
BibRef

Schiphorst, L., Doyran, M., Molenaar, S., Salah, A.A., Brinkkemper, S.,
Video2Report: A Video Database for Automatic Reporting of Medical Consultancy Sessions,
FG20(552-556)
IEEE DOI 2102
Cameras, Databases, Biomedical imaging, Feature extraction, Skeleton, Medical services, Lung, Machine Learning, Video Processing, LSTM BibRef

Ding, J., Xu, L., Guo, J., Dai, S.,
Human Detection In Dense Scene Of Classrooms,
ICIP20(618-622)
IEEE DOI 2011
Proposals, Detectors, Training, Object detection, Semantics, Feature extraction, Convolution, Human detection, discriminative part BibRef

Shen, C., Xue, M., Wang, X., Song, J., Sun, L., Song, M.,
Customizing Student Networks From Heterogeneous Teachers via Adaptive Knowledge Amalgamation,
ICCV19(3503-3512)
IEEE DOI 2004
computer aided instruction, learning (artificial intelligence), neural nets, heterogeneous teachers, selective learning scheme, task-specific knowledge BibRef

Dai, Z.C.[Zi-Chun], Sun, C.[Chao], Yu, X.G.[Xin-Guo], Xiang, Y.[Ying],
Detecting Global Exam Events in Invigilation Videos Using 3d Convolutional Neural Network,
PSIVT19(172-182).
Springer DOI 2003
Exam monitoring. BibRef

Li, X.T.[Xue-Ting], Liu, S.F.[Si-Fei], Kim, K.[Kihwan], Wang, X.L.[Xiao-Long], Yang, M.H.[Ming-Hsuan], Kautz, J.[Jan],
Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments,
CVPR19(12360-12368).
IEEE DOI 2002
what human poses are afforded by a given indoor environment. Do they sit, stand, etc. BibRef

Li, Y., Hung, Y.,
Feature Fusion of Face and Body for Engagement Intensity Detection,
ICIP19(3312-3316)
IEEE DOI 1910
neural networks, engagement detection, educational technology BibRef

Alkabbany, I., Ali, A., Farag, A., Bennett, I., Ghanoum, M., Farag, A.,
Measuring Student Engagement Level Using Facial Information,
ICIP19(3337-3341)
IEEE DOI 1910
Engagement level measurement, Machine Learning, Learning Disabilities BibRef

Canedo, D.[Daniel], Trifan, A.[Alina], Neves, A.J.R.[António J. R.],
Focus Estimation in Academic Environments Using Computer Vision,
IbPRIA19(I:620-628).
Springer DOI 1910
BibRef

Sarker, M.M.K.[M. Mostafa Kamal], Rashwan, H.A.[Hatem A.], Talavera, E.[Estefania], Banu, S.F.[Syeda Furruka], Radeva, P.[Petia], Puig, D.[Domenec],
MACNet: Multi-scale Atrous Convolution Networks for Food Places Classification in Egocentric Photo-Streams,
Egocentric18(V:423-433).
Springer DOI 1905
BibRef

Mery, D., Mackenney, I., Villalobos, E.,
Student Attendance System in Crowded Classrooms Using a Smartphone Camera,
WACV19(857-866)
IEEE DOI 1904
cameras, computer aided instruction, educational administrative data processing, Protocols BibRef

Singhal, A., Ali, M.R., Baten, R.A., Kurumada, C., Marvin, E.W., Hoque, M.E.,
Analyzing the Impact of Gender on the Automation of Feedback for Public Speaking,
FG18(607-613)
IEEE DOI 1806
Feature extraction, Gold, Interviews, Linear regression, Predictive models, Public speaking, Videos, Facial Analysis, Public Speaking BibRef

Sharma, R., Guha, T., Sharma, G.,
Multichannel Attention Network for Analyzing Visual Behavior in Public Speaking,
WACV18(476-484)
IEEE DOI 1806
data visualisation, face recognition, feedforward neural nets, learning (artificial intelligence), TED talk videos, YouTube BibRef

Jiang, H., Dykstra, K., Whitehill, J.,
Predicting When Teachers Look at Their Students in 1-on-1 Tutoring Sessions,
FG18(593-598)
IEEE DOI 1806
Cameras, Detectors, Face, History, Neural networks, Predictive models, Visualization, eye gaze prediction BibRef

Hulens, D.[Dries], Aerts, B.[Bram], Chakravarty, P.[Punarjay], Diba, A.[Ali], Goedemé, T.[Toon], Roussel, T.[Tom], Zegers, J.[Jeroen], Tuytelaars, T.[Tinne], van Eycken, L.[Luc], Van Gool, L.J.[Luc J.], van Hamme, H.[Hugo], Vennekens, J.[Joost],
The CAMETRON Lecture Recording System: High Quality Video Recording and Editing with Minimal Human Supervision,
MMMod18(I:518-530).
Springer DOI 1802
BibRef

Deng, Z.W.[Zhi-Wei], Navarathna, R.[Rajitha], Carr, P.[Peter], Mandt, S.[Stephan], Yue, Y.S.[Yi-Song], Matthews, I.[Iain], Mori, G.[Greg],
Factorized Variational Autoencoders for Modeling Audience Reactions to Movies,
CVPR17(6014-6023)
IEEE DOI 1711
Data models, Decoding, Machine learning, Motion pictures, Neural networks, Probabilistic logic, Tensile, stress BibRef

Cote, M., Dash, A., Albu, A.B.,
Look who is not talking: Assessing engagement levels in panel conversations,
ICPR16(2109-2114)
IEEE DOI 1705
Body regions, Computational modeling, Feature extraction, History, Pattern recognition, Visualization, behavioral patterns, group interaction, motion analysis, non-speaker identification, nonverbal communication, pixel change history, support vector machines, video, analysis BibRef