{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:27:49Z","timestamp":1792790869122,"version":"4.5.0"},"reference-count":80,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T00:00:00Z","timestamp":1623801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["01JD1811C"],"award-info":[{"award-number":["01JD1811C"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Processing visual stimuli in a scene is essential for the human brain to make situation-aware decisions. These stimuli, which are prevalent subjects of diagnostic eye tracking studies, are commonly encoded as rectangular areas of interest (AOIs) per frame. Because it is a tedious manual annotation task, the automatic detection and annotation of visual attention to AOIs can accelerate and objectify eye tracking research, in particular for mobile eye tracking with egocentric video feeds. In this work, we implement two methods to automatically detect visual attention to AOIs using pre-trained deep learning models for image classification and object detection. Furthermore, we develop an evaluation framework based on the VISUS dataset and well-known performance metrics from the field of activity recognition. We systematically evaluate our methods within this framework, discuss potentials and limitations, and propose ways to improve the performance of future automatic visual attention detection methods.<\/jats:p>","DOI":"10.3390\/s21124143","type":"journal-article","created":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T21:58:32Z","timestamp":1623880712000},"page":"4143","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Automatic Visual Attention Detection for Mobile Eye Tracking Using Pre-Trained Computer Vision Models and Human Gaze"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6730-2466","authenticated-orcid":false,"given":"Michael","family":"Barz","sequence":"first","affiliation":[{"name":"German Research Center for Artificial Intelligence (DFKI), Interactive Machine Learning Department, Stuhlsatzenhausweg 3, Saarland Informatics Campus D3_2, 66123 Saarbr\u00fccken, Germany"},{"name":"Applied Artificial Intelligence, Oldenburg University, Marie-Curie Str. 1, 26129 Oldenburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8857-8709","authenticated-orcid":false,"given":"Daniel","family":"Sonntag","sequence":"additional","affiliation":[{"name":"German Research Center for Artificial Intelligence (DFKI), Interactive Machine Learning Department, Stuhlsatzenhausweg 3, Saarland Informatics Campus D3_2, 66123 Saarbr\u00fccken, Germany"},{"name":"Applied Artificial Intelligence, Oldenburg University, Marie-Curie Str. 1, 26129 Oldenburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,16]]},"reference":[{"key":"ref_1","unstructured":"Holmqvist, K., and Andersson, R. (2011). Eye Tracking: A Comprehensive Guide to Methods, Paradigms and Measures, Lund Eye-Tracking Research Institute."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kurzhals, K., Bopp, C.F., B\u00e4ssler, J., Ebinger, F., and Weiskopf, D. (2014, January 10). Benchmark data for evaluating visualization and analysis techniques for eye tracking for video stimuli. Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization, BELIV \u201914, Paris, France.","DOI":"10.1145\/2669557.2669558"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1109\/TBME.2004.831523","article-title":"A new methodology for determining point-of-gaze in head-mounted eye tracking systems","volume":"51","author":"Yu","year":"2004","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Pfeiffer, T., Renner, P., and Pfeiffer-Le\u00dfmann, N. (2016, January 14). EyeSee3D 2.0: Model-based real-time analysis of mobile eye-tracking in static and dynamic three-dimensional scenes. Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, ETRA \u201916, Charleston, SC, USA.","DOI":"10.1145\/2857491.2857532"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Barz, M., Daiber, F., Sonntag, D., and Bulling, A. (2018, January 14). Error-Aware Gaze-Based Interfaces for Robust Mobile Gaze Interaction. Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications, Warsaw, Poland.","DOI":"10.1145\/3204493.3204536"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Mehlmann, G., H\u00e4ring, M., Janowski, K., Baur, T., Gebhard, P., and Andr\u00e9, E. (2014, January 12). Exploring a Model of Gaze for Grounding in Multimodal HRI. Proceedings of the 16th International Conference on Multimodal Interaction-ICMI \u201914, Istanbul, Turkey.","DOI":"10.1145\/2663204.2663275"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Barz, M., and Sonntag, D. (2016, January 12). Gaze-guided object classification using deep neural networks for attention-based computing. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct-UbiComp \u201916, Heidelberg, Germany.","DOI":"10.1145\/2968219.2971389"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1109\/TVCG.2016.2598695","article-title":"Visual Analytics for Mobile Eye Tracking","volume":"23","author":"Kurzhals","year":"2017","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_9","unstructured":"Machado, E., Carrillo, I., and Chen, L. (2019, January 19\u201323). Visual Attention-Based Object Detection in Cluttered Environments. Proceedings of the 2019 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computing, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld\/SCALCOM\/UIC\/ATC\/CBDCom\/IOP\/SCI), Leicester, UK."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Pontillo, D.F., Kinsman, T.B., and Pelz, J.B. (2010). SemantiCode: Using content similarity and database-driven matching to code wearable eyetracker gaze data. Eye Tracking Research and Applications Symposium (ETRA), ACM Press.","DOI":"10.1145\/1743666.1743729"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Toyama, T., Kieninger, T., Shafait, F., and Dengel, A. (2012, January 28). Gaze guided object recognition using a head-mounted eye tracker. Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA \u201912, Santa Barbara, CA, USA.","DOI":"10.1145\/2168556.2168570"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1109\/THMS.2019.2892919","article-title":"Software Architecture for Automating Cognitive Science Eye-Tracking Data Analysis and Object Annotation","volume":"49","author":"Panetta","year":"2019","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"key":"ref_13","unstructured":"Venuprasad, P., Xu, L., Huang, E., Gilman, A., Chukoskie, L., and Cosman, P. (2012, January 2). Analyzing Gaze Behavior Using Object Detection and Unsupervised Clustering. Proceedings of the ACM Symposium on Eye Tracking Research and Applications, Stuttgart, Germany."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Br\u00f4ne, G., Oben, B., and Goedem\u00e9, T. (2011, January 18). Towards a more effective method for analyzing mobile eye-tracking data: Integrating gaze data with object recognition algorithms. Proceedings of the 1st International Workshop on Pervasive Eye Tracking & Mobile Eye-Based Interaction, PETMEI \u201911, Beijing, China.","DOI":"10.1145\/2029956.2029971"},{"key":"ref_15","unstructured":"De Beugher, S., Br\u00f4ne, G., and Goedem\u00e9, T. (2014, January 5\u20138). Automatic analysis of in-the-wild mobile eye-tracking experiments using object, face and person detection. Proceedings of the 2014 International Conference on Computer Vision Theory and Applications (VISAPP), Lisbon, Portugal."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6","DOI":"10.16910\/jemr.11.6.6","article-title":"Automating areas of interest analysis in mobile eye tracking experiments based on machine learning","volume":"11","author":"Wolf","year":"2018","journal-title":"J. Eye Mov. Res."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Huang, C.M., and Mutlu, B. (2016, January 7\u201310). Anticipatory robot control for efficient human-robot collaboration. Proceedings of the 2016 11th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), Christchurch, New Zealand.","DOI":"10.1109\/HRI.2016.7451737"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1889681.1889687","article-title":"Performance metrics for activity recognition","volume":"2","author":"Ward","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1109\/TPAMI.2012.89","article-title":"State-of-the-Art in Visual Attention Modeling","volume":"35","author":"Borji","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_20","first-page":"222","article-title":"Eye movements and vision","volume":"6","author":"Yarbus","year":"1967","journal-title":"Neuropsychologia"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3559","DOI":"10.1016\/S0042-6989(01)00102-X","article-title":"In what ways do eye movements contribute to everyday activities?","volume":"41","author":"Land","year":"2001","journal-title":"Vis. Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"790","DOI":"10.1080\/13506280902793843","article-title":"Top-down control of eye movements: Yarbus revisited","volume":"17","author":"DeAngelus","year":"2009","journal-title":"Vis. Cogn."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1167\/7.14.16","article-title":"Task and context determine where you look","volume":"7","author":"Rothkopf","year":"2016","journal-title":"J. Vis."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2070719.2070720","article-title":"Introduction to the special issue on eye gaze in intelligent human-machine interaction","volume":"1","author":"Chai","year":"2012","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2499474.2499479","article-title":"Introduction to the special section on eye gaze and conversation","volume":"3","author":"Chai","year":"2013","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2893485","article-title":"Introduction to the special issue on new directions in eye gaze for interactive intelligent systems","volume":"6","author":"Nakano","year":"2016","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_27","first-page":"365","article-title":"Gaze-informed multimodal interaction","volume":"Volume 1","author":"Qvarfordt","year":"2017","journal-title":"The Handbook of Multimodal-Multisensor Interfaces: Foundations, User Modeling, and Common Modality Combinations"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"11:1","DOI":"10.1145\/2499474.2499480","article-title":"Gaze awareness in conversational agents: Estimating a user\u2019s conversational engagement from eye gaze","volume":"3","author":"Ishii","year":"2013","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_29","first-page":"4:1","article-title":"Prediction of Who Will Be the Next Speaker and When Using Gaze Behavior in Multiparty Meetings","volume":"6","author":"Ishii","year":"2016","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2499474.2499481","article-title":"Gaze and turn-taking behavior in casual conversational interactions","volume":"3","author":"Jokinen","year":"2013","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Prasov, Z., and Chai, J.Y. (2008, January 13). What\u2019s in a Gaze? The Role of Eye-gaze in Reference Resolution in Multimodal Conversational Interfaces. Proceedings of the 13th International Conference on Intelligent User Interfaces, Gran Canaria, Spain.","DOI":"10.1145\/1378773.1378777"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2882970","article-title":"See you see me: The role of Eye contact in multimodal human-robot interaction","volume":"6","author":"Xu","year":"2016","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2764921","article-title":"Context-aware automated analysis and annotation of social human-agent interactions","volume":"5","author":"Baur","year":"2015","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_34","unstructured":"Thomason, J., Sinapov, J., Svetlik, M., Stone, P., and Mooney, R.J. (2016, January 9). Learning Multi-modal Grounded Linguistic Semantics by Playing \u201cI Spy\u201d. Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, New York, NY, USA."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2070719.2070722","article-title":"Attentive documents: Eye tracking as implicit feedback for information retrieval and beyond","volume":"1","author":"Buscher","year":"2012","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Sattar, H., M\u00fcller, S., Fritz, M., and Bulling, A. (2015, January 7\u201312). Prediction of search targets from fixations in open-world settings. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298700"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Sattar, H., Bulling, A., and Fritz, M. (2017, January 22\u201329). Predicting the Category and Attributes of Visual Search Targets Using Deep Gaze Pooling. Proceedings of the 2017 IEEE International Conference on Computer Vision Workshop (ICCVW), Venice, Italy.","DOI":"10.1109\/ICCVW.2017.322"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/j.neucom.2020.01.028","article-title":"Deep gaze pooling: Inferring and visually decoding search intents from human gaze fixations","volume":"387","author":"Sattar","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_39","unstructured":"Trollmann, F., and Turhan, A.Y. (2018). Visual Search Target Inference using Bag of Deep Visual Words. KI 2018: Advances in Artificial Intelligence, Springer."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Barz, M., Stauden, S., and Sonntag, D. (2012, January 2). Visual Search Target Inference in Natural Interaction Settings with Machine Learning. Proceedings of the 2020 ACM Symposium on Eye Tracking Research & Applications, Stuttgart, Germany.","DOI":"10.1145\/3379155.3391314"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Bulling, A., Weichel, C., and Gellersen, H. (2013, January 27). EyeContext: Recognition of High-level Contextual Cues from Human Visual Behaviour. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France.","DOI":"10.1145\/2470654.2470697"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Steil, J., and Bulling, A. (2015, January 7). Discovery of everyday human activities from long-term visual behaviour using topic models. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing-UbiComp \u201915, Osaka, Japan.","DOI":"10.1145\/2750858.2807520"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Steil, J., M\u00fcller, P., Sugano, Y., and Bulling, A. (2018, January 3). Forecasting user attention during everyday mobile interactions using device-integrated and wearable sensors. Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI \u201918, Barcelona, Spain.","DOI":"10.1145\/3229434.3229439"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., and Schmid, C. (2012). Learning to Recognize Daily Actions Using Gaze. Computer Vision\u2013ECCV 2012, Springer.","DOI":"10.1007\/978-3-642-33709-3"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhefan Ye, Z., and Rehg, J.M. (2015, January 7\u201312). Delving into egocentric actions. Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298625"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Li, Y., Liu, M., and Rehg, J.M. (2018, January 8\u201314). In the Eye of Beholder: Joint Learning of Gaze and Actions in First Person Video. Proceedings of the The European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01228-1_38"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Shiga, Y., Toyama, T., Utsumi, Y., Kise, K., and Dengel, A. Daily activity recognition combining gaze motion and visual features. Proceedings of the UbiComp 2014-Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing.","DOI":"10.1145\/2638728.2641691"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2939381","article-title":"Added value of gaze-exploiting semantic representation to allow robots inferring human behaviors","volume":"7","author":"Minhas","year":"2017","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_49","unstructured":"Kurzhals, K., Rodrigues, N., Koch, M., Stoll, M., Bruhn, A., Bulling, A., and Weiskopf, D. (2012, January 2). Visual analytics and annotation of pervasive eye tracking video. Proceedings of the Eye Tracking Research and Applications Symposium (ETRA), Stuttgart, Germany."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2633043","article-title":"Inferring visualization task properties, user performance, and user cognitive abilities from eye gaze data","volume":"4","author":"Steichen","year":"2014","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1145\/3301400","article-title":"Comparing and Combining Interaction Data and Eye-tracking Data for the Real-time Prediction of User Cognitive Abilities in Visualization Tasks","volume":"10","author":"Conati","year":"2020","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"De Beugher, S., Ichiche, Y., Br\u00f4ne, G., and Goedem\u00e9, T. (2012, January 5). Automatic analysis of eye-tracking data using object detection algorithms. Proceedings of the 2012 ACM Conference on Ubiquitous Computing, UbiComp \u201912, Pittsburgh, PA, USA.","DOI":"10.1145\/2370216.2370363"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"19","DOI":"10.16910\/jemr.5.2.6","article-title":"Collecting and Analyzing Eye-Tracking Data in Outdoor Environments","volume":"5","author":"Evans","year":"2012","journal-title":"J. Eye Mov. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1177\/1541931213601362","article-title":"Making Sense of Mobile Eye-Tracking Data in the Real-World: A Human-in-the-Loop Analysis Approach","volume":"60","author":"Fong","year":"2016","journal-title":"Proc. Hum. Factors Ergon. Soc. Annu. Meet."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"52278","DOI":"10.1109\/ACCESS.2020.2980901","article-title":"ISeeColor: Method for Advanced Visual Analytics of Eye Tracking Data","volume":"8","author":"Panetta","year":"2020","journal-title":"IEEE Access"},{"key":"ref_56","unstructured":"S\u00fcmer, O., Goldberg, P., St\u00fcrmer, K., Seidel, T., Gerjets, P., Trautwein, U., and Kasneci, E. (2018, January 19\u201321). Teachers\u2019 Perception in the Classroom. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Salt Lake City, UT, USA."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Li, B., Wu, W., Wang, Q., Zhang, F., Xing, J., and Yan, J. (2019, January 15\u201320). SiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00441"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Cao, Q., Shen, L., Xie, W., Parkhi, O.M., and Zisserman, A. (2018, January 15\u201319). VGGFace2: A Dataset for Recognising Faces across Pose and Age. Proceedings of the 2018 13th IEEE International Conference on Automatic Face Gesture Recognition (FG 2018), Xi\u2019an, China.","DOI":"10.1109\/FG.2018.00020"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Kim, K.J., and Baek, N. (2019). Automated Analysis of Eye-Tracker-Based Human-Human Interaction Studies. Information Science and Applications 2018, Springer. Lecture Notes in Electrical Engineering.","DOI":"10.1007\/978-981-13-1056-0"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_61","first-page":"316","article-title":"Towards episodic memory support for dementia patients by recognizing objects, faces and text in eye gaze","volume":"Volume 9324","author":"Toyama","year":"2015","journal-title":"KI 2015: Advances in Artificial Intelligence"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., and Rabinovich, A. (2015, January 7\u201312). Going Deeper With Convolutions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","article-title":"ImageNet Large Scale Visual Recognition Challenge","volume":"115","author":"Russakovsky","year":"2015","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Dollar, P., and Girshick, R. (2017, January 22\u201329). Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref_65","first-page":"505","article-title":"Automated areas of interest analysis for usability studies of tangible screen-based user interfaces using mobile eye tracking","volume":"34","author":"Batliner","year":"2020","journal-title":"AI EDAM"},{"key":"ref_66","unstructured":"Howard, A.G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., and Adam, H. (2017). MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. CoRR."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Maire, M., Belongie, S.J., Bourdev, L.D., Girshick, R.B., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., and Zitnick, C.L. (2014). Microsoft COCO: Common Objects in Context. CoRR.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"3212","DOI":"10.1109\/TNNLS.2018.2876865","article-title":"Object Detection With Deep Learning: A Review","volume":"30","author":"Zhao","year":"2019","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (2016, January 27\u201330). Deep Residual Learning for Image Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Ma, M., Fan, H., and Kitani, K.M. (2016, January 27\u201330). Going Deeper into First-Person Activity Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.209"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Bertasius, G., Park, H.S., Yu, S.X., and Shi, J. (2016). First-Person Action-Object Detection with EgoNet. CoRR.","DOI":"10.15607\/RSS.2017.XIII.012"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Barz, M., Kapp, S., Kuhn, J., and Sonntag, D. (2021, January 25). Automatic Recognition and Augmentation of Attended Objects in Real-time using Eye Tracking and a Head-mounted Display. Proceedings of the ACM Symposium on Eye Tracking Research and Applications, ETRA \u201921 Adjunct, Virtual Event, Germany.","DOI":"10.1145\/3450341.3458766"},{"key":"ref_73","unstructured":"Wu, Y., Kirillov, A., Massa, F., Lo, W.Y., and Girshick, R. (2021, May 02). Detectron2. Available online: https:\/\/github.com\/facebookresearch\/detectron2."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Steil, J., Huang, M.X., and Bulling, A. (2018, January 14). Fixation detection for head-mounted eye tracking based on visual similarity of gaze targets. Proceedings of the Eye Tracking Research and Applications Symposium (ETRA), Warsaw, Poland.","DOI":"10.1145\/3204493.3204538"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Chen, C.S., Lu, J., and Ma, K.K. (2017). Fine-Tuning Deep Neural Networks in Continuous Learning Scenarios. Computer Vision\u2013ACCV 2016 Workshops: ACCV 2016 International Workshops, Taipei, Taiwan, 20\u201324 November 2016, Revised Selected Papers, Part III, Springer.","DOI":"10.1007\/978-3-319-54526-4"},{"key":"ref_76","unstructured":"Sonntag, D., Barz, M., Zacharias, J., Stauden, S., Rahmani, V., F\u00f3thi, \u00c1., and L\u00f6rincz, A. (2017). Fine-tuning deep CNN models on specific MS COCO categories. CoRR."},{"key":"ref_77","unstructured":"Simard, P., Amershi, S., Chickering, M., Edelman Pelton, A., Ghorashi, S., Meek, C., Ramos, G., Suh, J., Verwey, J., and Wang, M. (2017). Machine Teaching: A New Paradigm for Building Machine Learning Systems. CoRR."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3185517","article-title":"A Review of User Interface Design for Interactive Machine Learning","volume":"8","author":"Dudley","year":"2018","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Barz, M., Daiber, F., and Bulling, A. (2016, January 14). Prediction of Gaze Estimation Error for Error-Aware Gaze-Based Interfaces. Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, ETRA \u201916, Charleston, SC, USA.","DOI":"10.1145\/2857491.2857493"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Kapp, S., Barz, M., Mukhametov, S., Sonntag, D., and Kuhn, J. (2021). ARETT: Augmented Reality Eye Tracking Toolkit for Head Mounted Displays. Sensors, 21.","DOI":"10.3390\/s21062234"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/12\/4143\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:17:08Z","timestamp":1760163428000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/12\/4143"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,16]]},"references-count":80,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["s21124143"],"URL":"https:\/\/doi.org\/10.3390\/s21124143","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,16]]}}}