Faculty Profiles

Melnyk, K., Friedman, L., & Komogortsev, O. (2024). What can entropy metrics tell us about the characteristics of ocular fixation trajectories? Plos One, 19(1). https://doi.org/https://doi.org/10.1371/journal.pone.0291823

Fernandes, A., Murdison, S., Schuetz, I., Komogortsev, O., & Proulx, M. (2024). The Effect of Degraded Eye Tracking Accuracy on Interactions in VR. ACM. https://doi.org/https://doi.org/10.1145/3649902.3656369

Aziz, S. D., Lohr, D., Friedman, L., & Komogortsev, O. (2024). Evaluation of Eye Tracking Signal Quality for Virtual Reality Applications: A Case Study in the Meta Quest Pro. ACM. https://doi.org/https://dl.acm.org/doi/10.1145/3649902.3653347

Komogortsev, O., & Friedman, L. (2024). Evidence for five types of fixation during a random saccade eye tracking task and changes in fixation duration as a function of time-on-task. Plos One. https://doi.org/https://doi.org/10.1371/journal.pone.0310436

Burlingham, C., Sendhilnathan, N., Komogortsev, O., & Proulx, M. (2024). Motor “laziness” constrains fixation selection in real-world tasks. Proceedings of the National Academy of Sciences. https://doi.org/https://doi.org/10.1073/pnas.230223912

Raju, M. H., Friedman, L., Lohr, D., & Komogortsev, O. (2024). Per-Subject Oculomotor Plant Mathematical Models and the Reliability of Their Parameters. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 7(2). https://doi.org/https://doi.org/10.1145/3649902.3653353

Raju, M. H., Friedman, L., Lohr, D., & Komogortsev, O. (2024). Signal vs Noise in Eye-tracking Data: Biometric Implications and Identity Information Across Frequencies. https://doi.org/https://doi.org/10.1145/3649902.3653353

Katrychuk, D., & Komogortsev, O. (2024). Appearance-Based Gaze Estimation as a Benchmark for Eye Image Data Generation Methods. Sensors, 14(20). https://doi.org/https://doi.org/10.3390/app14209586

Lohr, D., Proulx, M. J., & Komogortsev, O. (2024). Establishing a Baseline for Gaze-driven Authentication Performance in VR: A Breadth-First Investigation on a Very Large Dataset. In IEEE International Joint Conference on Biometrics (IJCB) 2024 (pp. 1–10). IEEE. https://doi.org/10.1109/ijcb62174.2024.10744483

Friedman, L., Prokopenko, V., Djanian, S., Katrychuk, D., & Komogortsev, O. (2023). Factors affecting inter-rater agreement in human classification of eye movements: a comparison of three datasets. Behavior Research Methods, 55(1), 417–427. https://doi.org/https://doi.org/10.3758/s13428-021-01782-4

Lohr, D., Aziz, S. D., Friedman, L., & Komogortsev, O. (2023). GazeBaseVR, a large-scale, longitudinal, binocular eye-tracking dataset collected in virtual reality. Scientific Data, 10(1). Retrieved from https://www.nature.com/articles/s41597-023-02075-5

Aziz, S. D., Lohr, D., Stefanescu, R., & Komogortsev, O. (2023). Practical Perception-Based Evaluation of Gaze Prediction for Gaze Contingent Rendering (pp. 1–17).

Lohr, D., Johnson, S., Aziz, S. D., & Komogortsev, O. (2023). Demonstrating Eye Movement Biometrics in Virtual Reality. ACM.

Palmero, C., Komogortsev, O., Escalera, S., & Talathi, S. (2023). Multi-Rate Sensor Fusion for Unconstrained Near-Eye Gaze Estimation (pp. 1–8). ACM.

Raju, M. H., Friedman, L., Bouman, T., & Komogortsev, O. (2023). Filtering eye-tracking data from an EyeLink 1000: Comparing heuristic, Savitzky-Golay, IIR and FIR digital filters. Journal of Eye Movement Research, 14(3). Retrieved from https://bop.unibe.ch/JEMR/article/view/9888

Raju, M. H., Friedman, L., Bouman, T., & Komogortsev, O. (2023). Determining which sine wave frequencies correspond to signal and which correspond to noise in eye-tracking time-series. Journal of Eye Movement Research, 14(3). Retrieved from https://bop.unibe.ch/JEMR/article/view/9887

Komogortsev, O., & Lohr, D. (2022). Eye Know You Too: Toward Viable End-to-End Eye Movement Biometrics for User Authentication. Transactions on Information Forensics and Security (TIFS), 3151–3164. https://doi.org/0.1109/TIFS.2022.3201369

Wagle, N., Morkos, J., Liu, J., Greenstein, J., Gong, K., Gangan, I., … Green, K. (2022). Non-Eye Tracking, Deep Learning-enabled Detection of Nystagmus in Dizzy Patients.

Wagle, N., Morkos, J., Liu, J., Reith, H., Greenstein, J., Gong, K., … Green, K. (2022). aEYE: A deep learning system for video nystagmus detection. Frontiers in Neurology, 13. https://doi.org/10.3389/fneur.2022.963968

Friedman, L., Prokopenko, V., Djanian, S., Katrychuk, D., & Komogortsev, O. (2022). Factors affecting inter-rater agreement in human classification of eye movements: a comparison of three datasets. Behavior Research Methods, 1–11. https://doi.org/https://doi.org/10.3758/s13428-021-01782-4

Lohr, D., Griffith, H., & Komogortsev, O. (2022). Eye Know You: Metric Learning for End-to-End Biometric Authentication Using Eye Movements From a Longitudinal Dataset. IEEE Transactions on Biometrics, Behavior, and Identity Science, 4(2), 276–288. https://doi.org/10.1109/TBIOM.2022.3167633

Katrychuck, D., & Komogortsev, O. (2022). A study on the generalizability of Oculomotor Plant Mathematical Model. ACM. https://doi.org/https://doi.org/10.1145/3517031.3532523

Aziz, S., & Komogortsev, O. (2022). An Assessment of the Eye Tracking Signal Quality Captured in the HoloLens 2. ACM. https://doi.org/https://doi.org/10.1145/3517031.3529626

Raju, M., Lohr, D., & Komogortsev, O. (2022). Iris Print Attack Detection using Eye Movement Signals. ACM. https://doi.org/https://doi.org/10.1145/3517031.3532521

Friedman, L., Stern, H., Prokopenko, V., Djanian, S., Friffith, H., & Komogortsev, O. (2022). Biometric Performance as a Function of Gallery Size. Applied Sciences, 12(21). https://doi.org/https://doi.org/10.3390/app122111144

Aziz, S., Lohr, D. J., & Komogortsev, O. (2022). SynchronEyes: A Novel, Paired Data Set of Eye Movements Recorded Simultaneously with Remote and Wearable Eye-Tracking Devices. In 2022 Symposium on Eye Tracking Research and Applications. ACM. https://doi.org/10.1145/3517031.3532522

Cruz, R., Komogortsev, O., Frohman, E., & Frohman, T. (n.d.). Treating MS after surviving PML: Discrete strategies for rescue, remission, and recovery patient 2: From the National Multiple Sclerosis Society Case Conference Proceedings. Neurology Neuroimmunology & Neuroinflammation.

Frohman, E., Villemarette-Pittman, N., Rodriguez, A., Glanzman, R., Rugheimer, S., Komogortsev, O., … Frohman, T. (2021). Application of an evidence-based, out-patient treatment strategy for COVID-19: Multidisciplinary medical practice principles to prevent severe disease. Journal of the Neurological Sciences, 426.

Friedman, L., Lohr, D., Hanson, T., & Komogortsev, O. (2021). Angular offset distributions during fixation are, more often than not, multimodal. Journal of Eye Movement Research, 14(3).

Palmero, C., Sharma, A., Behrendt, K., Krishnakumar, K., Komogortsev, O., & Talathi, S. (2021). OpenEDS2020 Challenge on Gaze Tracking for VR: Dataset and Results. Sensors, 21(14).

Griffith, H., Lohr, D., Abdulin, E., & Komogortsev, O. (2021). GazeBase, a large-scale, multi-stimulus, longitudinal eye movement dataset. Nature: Scientific Data, 8.

Friedman, L., Hanson, T., & Komogortsev, O. (2021). Multimodality During Fixation–Part II: Evidence for Multimodality in Spatial Precision-Related Distributions and Impact on Precision Estimates. Journal of Eye Movement Research, 14(3).

Wagle, N., Morkos, J., Liu, J., Greenstein, J., Gong, K., Gangan, I., … Green, K. (n.d.). Deep Learning Model Detects Nystagmus from Video Recording.

Katrychuk, D., Griffith, H. K., & Komogortsev, O. (2020). A Calibration Framework for Photosensor-based Eye-Tracking System. In ACM Symposium on Eye Tracking Research and Applications (pp. 1--5).

Griffith, H. K., & Komogortsev, O. (2020). A Shift-Based Data Augmentation Strategy for Improving Saccade Landing Point Prediction. In ACM Symposium on Eye Tracking Research and Applications (pp. 1--6).

Griffith, H. K., & Komogortsev, O. (2020). Texture Feature Extraction From Free-Viewing Scan Paths Using Gabor Filters With Downsampling. In ACM Symposium on Eye Tracking Research and Applications (pp. 1--3).

Griffith, H. K., Lohr, D., Abdulin, E., & Komogortsev, O. (2020). GazeBase: A Large-Scale, Multi-Stimulus, Longitudinal Eye Movement Dataset. arXiv Preprint arXiv:2009.06171.

Chen, Y., Komogortsev, O., & Talathi, S. (2020). Domain Adaptation for Eye Segmentation.

Zhu, Y., Yan, Y., & Komogortsev, O. (2020). Hierarchical HMM for Eye Movement Classification (pp. 544–554).

Lohr, D., Aziz, S., & Komogortsev, O. (2020). Eye Movement Biometrics Using a New Dataset Collected in Virtual Reality (pp. 1–3).

Komogortsev, O., Cavin, R., & Palermo, C. (2020). Dataset for Eye Tracking on a Virtual Reality Platform.

Palermo, C., Komogortsev, O., & Talathi, S. (2020). Benefits of temporal information for appearance-based gaze estimation.

Friedman, L., Stern, H., Price, L. R., & Komogortsev, O. (2020). Why Temporal Persistence of Biometric Features, as Assessed by the Intraclass Correlation Coefficient, Is So Valuable for Classification Performance, 20(16).

Shen, Y., Komogortsev, O., & Talathi, S. S. (2020). Domain Adaptation for Eye Segmentation. In Lecture Notes in Computer Science (pp. 555–569). Springer International Publishing. https://doi.org/10.1007/978-3-030-66415-2_36

Lohr, D., Griffith, H., Aziz, S., & Komogortsev, O. (2020). A Metric Learning Approach to Eye Movement Biometrics. In 2020 IEEE International Joint Conference on Biometrics (IJCB) (pp. 1–7). IEEE. https://doi.org/10.1109/ijcb48548.2020.9304859

Katrychuk, D., Griffith, H., & Komogortsev, O. (2020). A Calibration Framework for Photosensor-based Eye-Tracking System. In ACM Symposium on Eye Tracking Research and Applications. ACM. https://doi.org/10.1145/3379156.3391370

Griffith, H., & Komogortsev, O. (2020). A Shift-Based Data Augmentation Strategy for Improving Saccade Landing Point Prediction. In ACM Symposium on Eye Tracking Research and Applications (pp. 1–6). ACM. https://doi.org/10.1145/3379157.3388935

Griffith, H. K., Aziz, S., & Komogortsev, O. (2020). Prediction of Oblique Saccade Trajectories Using Learned Velocity Profile Parameter Mappings. IEEE. https://doi.org/10.1109/CCWC47524.2020.9031274

Griffith, H. K., Katrychuk, D., & Komogortsev, O. (2019). Assessment of Shift-Invariant CNN Gaze Mappings for PS-OG Eye Movement Sensors.

Friedman, L., & Komogortsev, O. (2019). Assessment of the Effectiveness of 7 Biometric Feature  Normalization Techniques. Transactions on Information Forensics and Security, 14(10), 2528–2536.

Katrychuk, D., Griffith, H. K., & Komogortsev, O. (2019). Power-efficient and shift-robust eye-tracking sensor for portable VR headsets (pp. 1–9). ACM.

Katrychuk, D., Griffith, H. K., & Komogortsev, O. (2019). Power-efficient and shift-robust eye-tracking sensor for portable VR headsets.

Friedman, L., Stern, H. S., Prokopenko, V., Djanian, S., Griffith, H. K., & Komogortsev, O. (2019). Biometric Performance as a Function of Gallery Size. arXiv Preprint arXiv:1906.06272.

Reppert, T., Rigas, I., Herzfeld, D., Sedaghat-Nejad, E., Komogortsev, O., & Shadmehr, R. (2018). Movement vigor as a trait-like attribute of individuality. Journal of Neurophysiology, 120(2), 741–757.

Rigas, I., Raffle, H., & Komogortsev, O. (2018). Photosensor Oculography: Survey and Parametric Analysis of Designs Using Model-Based Simulation. IEEE Transactions on Human-Machine Systems, PP(99), 741–757.

Rigas, I., Friedman, L., & Komogortsev, O. V. (2018). Study of an Extensive Set of Eye Movement Features: Extraction Methods and Statistical Analysis. Journal of Eye Movement Research, 10(4).

Friedman, L., Rigas, I., Abdulin, E., & Komogortsev, O. (2018). A Novel Evaluation of Two Related, and Two Independent Algorithms for Eye Movement Classification during Reading. Behavioral Research Methods (BRM) Journal, 50(4), 1374–1397.

Griffith, H. K., Biswas, S., & Komogortsev, O. (2018). Towards Reduced Latency in Saccade Landing Position Prediction Using Velocity Profile Methods (pp. 79–91). Springer.

Griffith, H. K., Biswas, S., & Komogortsev, O. (2018). Towards improved saccade landing position estimation using velocity profile methods. IEEE.

Zemblys, R., & Komogortsev, O. (2018). Developing photo-sensor oculography (PS-OG) system for virtual reality headsets.

Lohr, D., Berndt, S., & Komogortsev, O. (2018). An implementation of eye movement-driven biometric in virtual reality.

Zemblys, R., & Komogortsev, O. (2018). Making stand-alone PS-OG technology tolerant to the equipment shifts. ACM.

Friedman, L., Nixon, M., & Komogortsev, O. (2017). Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases. PloS One.

Rigas, I., & Komogortsev, O. (2017). Hybrid PS-V Technique: A Novel Sensor Fusion Approach for Fast Mobile Eye-Tracking with Sensor-Shift Aware Correction. IEEE Sensors Journal.

Lohr, D., & Komogortsev, O. (2017). A Comparison of Smooth Pursuit- and Dwell-based Selection at Multiple Levels of Spatial Accuracy. ACM Conference on Human Factors in Computing Systems (CHI).

Abdulin, E., & Komogortsev, O. (2017). Study of Additional Eye-Related Features for Future Eye-Tracking Techniques,. ACM.

Choem, Y., Nguyen, K., Komogortsev, O., & Gutierrez-Osuna, R. (2017). Explanation of the Perceptual Oblique Effect Based on the Fidelity of Oculomotor Control During Saccades. IEEE.

Rigas, I., & Komogortsev, O. (2017). Current research in eye movement biometrics: An analysis based on BioEye 2015 competition. Journal of Image and Vision Computing, 129–141.

Zemblys, R., Niehorster, D., Komogortsev, O., & K. (2017). Using machine learning to detect events in eye-tracking data. Behavioral Research Methods.

Abdulin, E., Friedman, L., & Komogortsev, O. (2017). Method to Detect Eye Position Noise from Video-Oculography when Detection of Pupil or Corneal Reflection Position Fails (p. 20). ArXiv. Retrieved from https://arxiv.org/pdf/1709.02700.pdf

Friedman, L., & Komogortsev, O. (2017). MNH Code. Retrieved from https://digital.library.txstate.edu/handle/10877/6874

Rigas, I., & Komogortsev, O. (2017). Feature Extraction Code and Data. Retrieved from https://digital.library.txstate.edu/handle/10877/6904

Nguyen, K. N., Liu, X., Komogortsev, O., Gutierrez-Osuna, R., & Choe, Y. (2017). Explanation of the perceptual oblique effect based on the fidelity of oculomotor control during saccades. In 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 15–20). IEEE. https://doi.org/10.1109/devlrn.2017.8329781

Abdulin, E., Friedman, L., & Komogortsev, O. V. (2017). Method to Detect Eye Position Noise from Video-Oculography when Detection of Pupil or Corneal Reflection Position Fails. arXiv, https://arxiv.org/abs/1709.02700. Retrieved from https://arxiv.org/abs/1709.02700

Rigas, I., Abdulin, E., & Komogortsev, O. (2016). Towards a multi-source fusion approach for eye movement-driven recognition. Information Fusion, 32(B), 13–25.

Karpov, A., Komogortsev, O., & Holland, C. (2016). Oculomotor Plant Characteristics: The Effects of Environment and Stimulus. IEEE Transactions on Information Forensics and Security, 11(3), 621–632.

Rigas, I., Komogortsev, O., & Shadmehr, R. (2016). Biometric Recognition via the Complex Eye Movement Behavior and the Incorporation of Saccadic Vigor and Acceleration Cues. ACM Transactions on Applied Perception, 13(2), 1–21.

Komogortsev, O., Rigas, I., & Abdulin, E. (2016). Eye Movement Biometrics on Wearable Devices: What Are the Limits? (pp. 1–6).

Lohr, D. J., Abdulin, E., & Komogortsev, O. (2016). Detecting the onset of eye fatigue in a live framework (pp. 1–2).

Friedman, L., Rigas, I., Nixon, M., & Komogortsev, O. (2016). Method to Assess the Temporal Persistence of Potential Biometric Features: Application to Oculomotor, and Gait-Related Databases.

Zborowski, A., Komogortsev, O., Ceballos, N., Treffalls, J., & Graham, R. (2016). “Food preferences and gaze patterns to complex food images.”

Gobert, D., Komogortsev, O., Nelson, S. M., Kerby, J. L., Buchner, S. A., & Rouse, D. A. (2016). “Oculomotor Behavior Profile: Biometric Indicator of Post-Concussion Recovery.”

Rigas, I., & Komogortsev, O. (2015). Current research in eye movement biometrics: An analysis based on BioEye 2015 competition. Journal of Image and Vision Computing, 58.

Rigas, I., & Komogortsev, O. (2015). Eye movement-driven defense against iris print-attacks. Elsevier Journal Pattern Recognition Letters, Special Issue – Soft Biometrics, 68(P2), 316–326.

Komogortsev, O., Karpov, A., & Holland, C. (2015). Attack of Mechanical Replicas: Liveness Detection With Eye Movements. IEEE Transactions on Information Forensics and Security, 10(4), 716–725.

Komogortsev, O., & Rigas, I. (2015). IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), 1–8.

Abdulin, E., & Komogortsev, O. (2015). Person Verification via Eye Movement-driven Text Reading Model (pp. 1–8).

Gias, I., & Komogortsev, O. (2015). Single-Pixel Eye Tracking via Patterned Contact Lenses: Design and Evaluation in HCI Domain (pp. 1–6).

Abdulin, E., & Komogortsev, O. (2015). User Eye Fatigue Detection via Eye Movement Behavior (pp. 1–6).

Komogortsev, O., & Rigas, I. (2015). BioEye 2015: Competition on Biometrics via Eye Movements (pp. 1–8).

Komogortsev, O., Holland, C., Karpov, A., & Price, L. R. (2014). Biometrics via Oculomotor Plant Characteristics: Impact of Parameters in Oculomotor Plant Model. ACM Transactions on Applied Perception, 11(4), 1–17.

Rigas, I., & Komogortsev, O. (2014). Biometric Recognition via Probabilistic Spatial Projection of Eye Movement Trajectories in Dynamic Visual Environments. IEEE Transactions on Information Forensics and Security, 9(10), 1743–1754.

Tamir, D. E., Dasari, D. K. V., Komogortsev, O., LaKomski, G. R., & Mueller, C. J. (2014). “Detecting Software Usability Deficiencies Through Pinpoint Analysis.” International Journal on Advances in Software, 7(1 & 2), 44–62.

Rigas, I., & Komogortsev, O. (2014). Gaze Estimation as a Framework for Iris Liveness Detection (pp. 1–8).

Komogortsev, O., & Holland, C. (2014). The Application of Eye Movement Biometrics in the Automated Detection of Mild Traumatic Brain Injury (pp. 1–6).

Rigas, I., & Komogortsev, O. (2014). Biometric recognition via fixation density maps, In Proceedings of SPIE Defence+Security (DDS) (pp. 1–10).

Komogortsev, O., Karpov, A., & Holland, C. (2014). Template aging in eye movement-driven biometrics, In Proceedings of SPIE Defence+Security (DDS) (pp. 1–10).

Komogortsev, O., & Holland, C. (2014). Software Framework for an Ocular Biometric System (pp. 1–2).

Holland, C., & Komogortsev, O. (2013). “Complex Eye Movement Pattern Biometrics: The Effects of Environment and Stimulus.” IEEE Transactions on Information Forensics and Security, 8(12), 2155–2126.

Komogortsev, O., Holland, C., Jayarathna, S., & Karpov, A. (2013). “2D Linear Oculomotor Plant Mathematical Model: Verification and Biometric Applications.” ACM Transactions on Applied Perception, 10(4), 1–18.

Mueller, C., Tamir, D., & Komogortsev, O. (2013). “An Effort-Based Framework for Evaluating Software Usability Design.” ARPN Journal of Systems and Software, 3(4), 65–77.

Komogortsev, O., & Karpov, A. (2013). “Automated Classification and Scoring of Smooth Pursuit Eye Movements in Presence of Fixations and Saccades.” Journal of Behavioral Research Methods, 45, 203–215.

Komogortsev, O., & Holland, C. (2013). Biometric Authentication via Complex Oculomotor Behavior (pp. 1–8).

Komogortsev, O., & Karpov, A. (2013). Liveness Detection via Oculomotor Plant Characteristics: Attack of Mechanical Replicas (pp. 1–8).

Holland, C., & Komogortsev, O. (2013). Complex Eye Movement Pattern Biometrics: Analyzing Fixations and Saccades.

Brooks, M., Aragon, C., & Komogortsev, O. (2013). Perceptions of Interfaces for Eye Movement Biometrics (pp. 1–8).

Dasari, D., Tamir, D., Komogortsev, O., LaKomski, G., & Mueller, C. (2013). Pinpoint Analysis of Software Usability (pp. 1–9).

Holland, C., Garza, A., Kurtova, E., Cruz, J., & Komogortsev, O. (2013). Usability Evaluation of Eye Tracking on an Unmodified Common Tablet (pp. 1–6).

Fares, R., Fang, S., & Komogortsev, O. (2013). “Can We Beat the Mouse with MAGIC?” (pp. 1–4).

Komogortsev, O., Brooks, M., & Aragon, C. (2013). Identifying people by eye movements potential replacement for passwords. SPIE News Room.

Komogortsev, O., & Tamir, D. (2012). “A Learning-based Framework for Evaluating Software Usability.” ARPN Journal of Systems and Software, 2(2), 1–39.

Komogortsev, O., Karpov, A., Holland, C., & Proença, H. P. (2012). “Multimodal Ocular Biometrics Approach: A Feasibility Study” (pp. 1–8).

Holland, C., & Komogortsev, O. (2012). “Biometric Verification via Complex Eye Movements: The Effects of Environment and Stimulus” (pp. 1–8).

Kasprowki, P., Komogortsev, O., & Karpov, A. (2012). “First Eye Movement Verification and Identification Competition at BTAS 2012.”

Fares, R., Downing, D. T., & Komogortsev, O. (2012). “Magic-Sense: Dynamic Cursor Sensitivity-Based Magic Pointing” (pp. 1–6).

Holland, C., & Komogortsev, O. (2012). “Eye Tracking on Unmodified Common Tablets: Challenges and Solutions” (pp. 1–4).

Holland, C., Komogortsev, O., & Tamir, D. (2012). “Identifying Usability Issues via Algorithmic Detection of Excessive Visual Search” (pp. 1–10).

Komogortsev, O., Karpov, A., & Holland, C. (2012). CUE: Counterfeit-resistant Usable Eye-based Authentication via Scanpaths and Oculomotor Plant Characteristics (pp. 1–10).

Komogortsev, O., Karpov, A., Price, L., & Aragon, C. (2012). Biometric Authentication via Oculomotor Plant Characteristic (pp. 1–8).

Komogortsev, O., Holland, C., & Jayarathna, S. (2012). Two-Dimensional Linear Homeomorphic Oculomotor Plant Mathematical Model. Retrieved from https://digital.library.txstate.edu/handle/10877/4156

Komogortsev, O., Dai, Z., & Gobert, D. (2012). Automated Classification of Complex Oculomotor Behavior. Retrieved from https://digital.library.txstate.edu/handle/10877/4157

Komogortsev, O., Ryu, S., & Koh, D. H. (2012). Fast Target Selection via Saccade-driven Methods. Retrieved from https://digital.library.txstate.edu/handle/10877/4158

Graham, R., Treffalls, J., Ceballos, N. A., & Komogortsev, O. (2012). “Gaze patterns to food images are modulated by body mass index and gender: An eye-tracking study.”

Czyzewska, M., Nolan, A. E., Vanstone, J. E., & Komogortsev, O. (2012). “Visual attention to food ads and processing demands of task: Eye-tracker study.”

Graham, R., Hoover, A., Ceballos, N., & Komogortsev, O. (2011). “Body mass index moderates gaze orienting biases and pupil diameter to high and low calorie food images,.” Journal of Appetite, 56(3), 577–586.

Holland, C., & Komogortsev, O. (2011). Biometric Identification via Eye Movement Scanpaths in Reading (pp. 1–8).

Brooks, M., Aragon, C., & Komogortsev, O. (2011). User Centered Design and Evaluation of an Eye Movement-based Biometric Authentication System (pp. 1–2).

Komogortsev, O., Holland, C., & Camou, J. (2011). “Adaptive Eye-Gaze-Guided Interfaces: Design & Performance Evaluation,.”

Komogortsev, O., Tamir, D., Mueller, C., Camou, J., & Holland, C. (2011). “EMA: Automated Eye-movement-driven Approach for Identification of Usability Issues,” (pp. 1–10).

Tamir, D., Komogortsev, O., Mueller, C., Venkata, D., KaKomski, G. R., & Jamnagarwala, A. M. (2011). “Detection of Software Usability Deficiencies,” (pp. 1–10).

Karpov, A., & Komogortsev, O. (2011). Automated Classification and Scoring of Smooth Pursuit Eye Movements in Presence of Fixations and Saccades.

Komogortsev, O., Karpov, A., & Aragon, C. (2011). Biometric Authentication via Anatomical Characteristics of the Oculomotor Plant.

Philips, C., & Komogortsev, O. (2011). Impact of Resolution and Blur on Iris Identification.

Jayarathna, U. K. S., Holland, C., & Komogortsev, O. (2011). Two-Dimensional Linear Homeomorphic Oculomotor Plant Mathematical Model Equations.

Komogortsev, O., Holland, C., Tamir, D., & Mueller, C. (2011). Aiding usability evaluation via detection of excessive visual search. In CHI ’11 Extended Abstracts on Human Factors in Computing Systems (pp. 1825–1830). ACM. https://doi.org/10.1145/1979742.1979868

Komogortsev, O., Gobert, D. V., Jayarathna, U. K. S., Koh, D. H., & Gowda, S. M. (2010). “Standardization of Automated Analyses of Oculomotor Fixation and Saccadic Behaviors,.” Transactions on Biomedical Engineering, 57, 2635–2645.

Koh, D. H., Gowda, M., & Komogortsev, O. (2010). “Real Time Eye Movement Identification Protocol,” (pp. 1–6).

Komogortsev, O., Jayarathna, U. K. S., Aragon, C. R., & Mechehoul, M. (2010). “Biometric Identification via an Oculomotor Plant Mathematical Model,” (pp. 1–4).

Komogortsev, O., Jayarathna, U. K. S., Koh, D. H., & Gowda, M. (2010). “Qualitative and Quantitative Scoring and Evaluation of the Eye Movement Classification Algorithms,” (pp. 1–4).

Mechehoul, M., Jayarathna, S., & Komogortsev, O. (2010). “Statistical Approach to Person Identification via Unique Properties of the Oculomotor Plant.” Retrieved from http://ecommons.txstate.edu/cscitrep/20

Komogortsev, O., Tamir, D., & Mueller, C. J. (2010). “The Usability of DeltaV Control Studio Pilot Study Report.”

Sewell, W., & Komogortsev, O. (2010). Real Time Eye Gaze Tracking With an Unmodified Commodity Webcam Employing a Neural Network (pp. 1–6).

Vining, D. J., Cleveland, D., Wang, J., & Komogortsev, O. (2010). “Principles and Radiologic Applications of Eye-tracking Technology,.”

Ceballos, N., & Komogortsev, O. (2010). "Innovative Applications of Oculomotor Plant Metrics as Predictors of Social Drinking Levels and Attentional Biases to Alcohol-Related Stimuli”.

Hoover, A., Ceballos, N., Komogortsev, O., & Graham, R. (2010). “Effects of hunger and body mass index on attentional capture by high and low calorie food images: An eye-tracking study.”

Gobert, D., & Komogortsev, O. (2010). “Computerized Assessment of Oculomotor Dysfunction in Persons with mTBI.”

Komogortsev, O. (2009). “Gaze-contingent video compression with targeted gaze containment performance,.” Journal of Electronic Imaging, 18, 033001–033010.

Komogortsev, O., & Khan, J. (2009). “Eye Movement Prediction by Oculomotor Plant Kalman Filter with Brainstem Control,.” Journal of Control Theory and Applications, 7, 14–22.

Komogortsev, O., Ryu, Y. S., & Koh, D. H. (2009). “Quick Models for Saccade Amplitude Prediction,.” Journal of Eye Movement Research, 3, 1–13.

Fuhrmann, S., Komogortsev, O., & Tamir, D. (2009). “Investigating Hologram-Based Route Planning,.” Transactions in GIS, 13, 177–196.

Komogortsev, O., Ryu, Y. S., Koh, D. H., & Gowda, S. A. M. (2009). “Instantaneous Saccade Driven Eye Gaze Interaction,” (pp. 1–8).

Feldman, L., Mueller, C., Komogortsev, O., & Tamir, D. (2009). “Usability Testing with Total-Effort Metrics,” (pp. 426–429).

Komogortsev, O., Koh, D. H., & Gowda, S. A. M. (2009). “Input evaluation of an eye-gaze-guided interface: kalman filter vs. velocity threshold eye movement identification,” (pp. 197–202).

Komogortsev, O., Mueller, C., Tamir, D., & Feldman, L. (2009). “An Effort Based Model of Software Usability,” (pp. 1–8).

Mueller, C., Tamir, D., Komogortsev, O., & Feldman, L. (2009). “An Economical Approach to Usability Testing,” (pp. 124–129).

Mueller, C., Tamir, D., Komogortsev, O., & Feldman, L. (2009). “Using Designer’s Effort for User Interface Evaluation,” (pp. 1–6).

Komogortsev, O., Jayarathna, U. K. S., Aragon, C. R., & Mechehoul, M. (2009). “Biometric Identification via an Oculomotor Plant Mathematical Model,.” Retrieved from http://ecommons.txstate.edu/

Komogortsev, O., Jayarathna, U. K. S., Koh, D. H., & Gowda, S. M. (2009). “Qualitative and Quantitative Scoring and Evaluation of the Eye Movement Classification Algorithms,.” Retrieved from http://ecommons.txstate.edu/

Ceballos, N., Komogortsev, O., & Turner, G. M. (2009). “Ocular Imaging of Attentional Bias Among College Students: Automatic and Controlled Processing of Alcohol- Related Scenes,.” Journal of Studies on Alcohol and Drugs, 1–8.

Fuhrmann, S., Komogortsev, O., & Tamir, D. (2009). “Assessing hologram-based route planning.”

Komogortsev, O., Ryu, Y., & Koh, D. (2009). Saccade Amplitude Prediction Models. Retrieved from http://cs.txstate.edu/~ok11/ TR2009_01_07_Saccade_KoRyKo.pdf

Komogortsev, O., & Khan, J. I. (2008). “Predictive real-time perceptual compression based on eye-gaze-position analysis,.” ACM Trans. Multimedia Comput. Commun. Appl., 4, 1–16.

Komogortsev, O., Khan, V., & Khan, J. (2008). “Eye Movement Prediction by Kalman Filter with Integrated Linear Horizontal Oculomotor Plant Mechanical Model,” (pp. 229–236).

Komogortsev, O., & Jayarathna, U. K. S. (2008). “2D Oculomotor Plant Mathematical Model for eye movement simulation,” (pp. 1–8).

Tamir, D., Komogortsev, O., & Mueller, C. J. (2008). An effort and time based measure of usability (pp. 47–52).

Komogortsev, O., & Jayarathna, U. K. S. (2008). 2D Oculomotor Plant Mathematical Model Equations. Retrieved from http://cs.txstate.edu/~ok11/TR2008_05_30_2DOPMM_KoJa.pdf

Komogortsev, O., & Khan, J. (2007). “Perceptual Multimedia Compression based on the Predictive Kalman Filter Eye Movement Modeling,” (pp. 1–12).

Komogortsev, O., & Khan, J. (2007). “Kalman Filtering in the Design of Eye-Gaze-Guided Computer Interfaces,” (pp. 1–10).

Khan, J., & Komogortsev, O. (2006). “A Hybrid Scheme for Perceptual Object Window Design with Joint Scene Analysis and Eye-Gaze Tracking for Media Encoding based on Perceptual Attention,.” Journal of Electronic Imaging, 15(2), 023018-01-023018–12.

Komogortsev, O., & Khan, J. (2006). “Perceptual Attention Focus Prediction for Multiple Viewers in Case of Multimedia Perceptual Compression with Feedback Delay,” (pp. 101–108).

Komogortsev, O., & Khan, J. (2005). “Perceptual media compression for multiple viewers with feedback delay,” (pp. 1–1).

Khan, J., & Komogortsev, O. (2004). “A Hybrid Scheme for Perceptual Object Window Design with Joint Scene Analysis and Eye-Gaze Tracking for Media Encoding based on Perceptual Attention,” (pp. 1341–1352).

Khan, J., & Komogortsev, O. (2004). “Perceptual video compression with combined scene analysis and eye-gaze tracking,” (pp. 57–57).

Komogortsev, O., & Khan, J. (2004). Predictive Perceptual Compression for Real Time Video Communication (pp. 220–227).

Komogortsev, O., & Khan, J. I. (2004). “Contour Approximation for Faster Object-based Transcoding with Higher Perceptual Quality,” (pp. 441–446).

Komogortsev, O. (2003). “Contour Approximation Can Lead to Faster Object Based Transcoding with Higher Perceptual Quality.” Retrieved from , http://www.medianet.kent.edu/techreports/TR-2003-01-01-focusapproximation-KK.pdf.

Komogortsev, O., Khan, Y., Patel, J. S. D., Oh, W., Guo, Z., Gu, W., & Mail, P. (2002). Resource Adaptive Netcentric Systems on Active Network: a Self-Organizing  Video Stream that Automorphs itself while in Transit Via a Quasi-Active Network (pp. 409–426).

Khan, J., & Komogortsev, O. (2002). “Dynamic Gaze Span Window based Foveation for Perceptual Media Streaming”,. Retrieved from http://www.medianet.kent.edu/techreports/TR-2002-11-01-focus-KK.pdf.

Khan, J., & Komogortsev, O. (2002). “Impact on Stream Compression and Video Quality Motion Vector Reuse Transcoding.” Retrieved from http://www.medianet.kent.edu/labarea/student-reports/mv_bypass_paper3-oleg.doc

Komogortsev, O., Khan, J. I., Yang, S. S., Gu, Q., Patel, D., Mail, P., … Guo, Z. (2001). “Resource adaptive netcentric systems: a case study with SONET - a self-organizing network embedded transcoder,” (pp. 1–4).