Publications Citing Our Dataset
Welcome to our curated collection of research articles that have employed our Driver Fatigue Detection dataset. This page provides a comprehensive overview of the diverse scholarly articles, detailing how our dataset has been instrumental in advancing research within the fields of driver safety, fatigue detection, and beyond.
Our dataset’s unique multimodal approach, incorporating thermal, depth map, and visible light imagery, offers researchers a rich foundation for exploring and developing advanced detection systems. These publications reflect the broad applicability of the data and highlight significant advancements in automatic systems, which are crucial for enhancing road safety and understanding driver behavior under various conditions.
A New Benchmark Collection for Driver Fatigue Research
Authors: Małecki, K., Forczmański, P., Nowosielski, A., Smoliński, A., Ozga, D.
Published in: Progress in Computer Recognition Systems, Springer, 2020, pp. 295-304
The article presents an original benchmark database for testing methods and algorithms for driver fatigue detection, including blinking, squinting, rubbing eyes, yawning, and head movements. The data was acquired using thermal, depth map, and visible light cameras under conditions mimicking a driver’s work environment.
@InProceedings{Malecki2020_benchmark, author = {Ma{\l}ecki, Krzysztof and Forczma{\'{n}}ski, Pawe{\l} and Nowosielski, Adam and Smoli{\'{n}}ski, Anton and Ozga, Daniel}, title = {A New Benchmark Collection for Driver Fatigue Research Based on Thermal, Depth Map and Visible Light Imagery}, booktitle = {Progress in Computer Recognition Systems}, year = {2020}, publisher = {Springer International Publishing}, pages = {295--304}, doi = {10.1007/978-3-030-19738-4_30},}Małecki, K., Forczmański, P., Nowosielski, A., Smoliński, A., & Ozga, D. (2020). A New Benchmark Collection for Driver Fatigue Research Based on Thermal, Depth Map and Visible Light Imagery. In _Progress in Computer Recognition Systems_ (pp. 295-304). Springer International Publishing.Małecki, Krzysztof, et al. "A New Benchmark Collection for Driver Fatigue Research Based on Thermal, Depth Map and Visible Light Imagery." _Progress in Computer Recognition Systems_, edited by Robert Burduk et al., Springer International Publishing, 2020, pp. 295-304.Supporting Driver Physical State Estimation by Means of Thermal Image Processing
Authors: Forczmański, P., Smoliński, A.
Published in: Computational Science — ICCS 2021, Springer, 2021, pp. 149-163
This paper addresses the problem of estimating a driver’s physical state by analyzing facial portraits captured in the thermal spectrum. The algorithm involves detection, tracking, and classification of facial regions and features, demonstrating its effectiveness even in adverse lighting conditions.
@InProceedings{Forczmanski2021_driver, author = {Forczma{\'{n}}ski, Pawe{\l} and Smoli{\'{n}}ski, Anton}, title = {Supporting Driver Physical State Estimation by Means of Thermal Image Processing}, booktitle = {Computational Science -- ICCS 2021}, year = {2021}, publisher = {Springer International Publishing}, pages = {149--163}, doi = {10.1007/978-3-030-77977-1_12},}Forczmański, P., & Smoliński, A. (2021). Supporting Driver Physical State Estimation by Means of Thermal Image Processing. In _Computational Science -- ICCS 2021_ (pp. 149-163). Springer International Publishing.Forczmański, Paweł, and Anton Smoliński. "Supporting Driver Physical State Estimation by Means of Thermal Image Processing." _Computational Science -- ICCS 2021_, edited by Maciej Paszynski et al., Springer International Publishing, 2021, pp. 149-163.Multispectral Data Acquisition in the Assessment of Driver’s Fatigue
Authors: Małecki, K., Nowosielski, A., Forczmański, P.
Published in: Smart Solutions in Today’s Transport, Springer, 2017, pp. 320-332
Many factors contribute to road accidents, with driver behavior and fatigue being the most significant. This paper presents characteristics of selected multispectral data (visual image, depth map, thermal image) used for automatic assessment of driver fatigue. A simulator station, mimicking a driver’s cabin and equipped with various video sensors and monitors showing real driving situations, was developed for data acquisition.
@InProceedings{Malecki2017_multispectral, author = {Ma{\l}ecki, Krzysztof and Nowosielski, Adam and Forczma{\'{n}}ski, Pawe{\l}}, title = {Multispectral Data Acquisition in the Assessment of Driver's Fatigue}, booktitle = {Smart Solutions in Today's Transport}, year = {2017}, publisher = {Springer International Publishing}, pages = {320--332}, doi = {10.1007/978-3-319-66251-0_26},}Małecki, K., Nowosielski, A., & Forczmański, P. (2017). Multispectral Data Acquisition in the Assessment of Driver's Fatigue. In _Smart Solutions in Today's Transport_ (pp. 320-332). Springer International Publishing.Małecki, Krzysztof, Adam Nowosielski, and Paweł Forczmański. "Multispectral Data Acquisition in the Assessment of Driver's Fatigue." _Smart Solutions in Today's Transport_, Springer International Publishing, 2017, pp. 320-332.Eyes State Detection in Thermal Imaging
Authors: Forczmański, P., Smoliński, A.
Published in: Image Processing and Communications, Springer, 2020, pp. 22-29
This paper discusses the analysis of facial areas captured in thermal spectrum to estimate the drowsiness of observed persons. The state of eyes is considered crucial, and a Gabor filtering-based approach is applied to classify the eyes’ state. This approach allows for capturing eye states in adverse lighting conditions, showing promising results in simulated cabin environments.
@InProceedings{10.1007/978-3-030-31254-1_4, author = {Forczma{\'{n}}ski, Pawe{\l} and Smoli{\'{n}}ski, Anton}, title = {Eyes State Detection in Thermal Imaging}, booktitle = {Image Processing and Communications}, year = {2020}, publisher = {Springer International Publishing}, pages = {22--29},}Forczmański, P., & Smoliński, A. (2020). Eyes State Detection in Thermal Imaging. In _Image Processing and Communications_ (pp. 22-29). Springer International Publishing.Forczmański, Paweł, and Anton Smoliński. "Eyes State Detection in Thermal Imaging." _Image Processing and Communications_, Springer International Publishing, 2020, pp. 22-29.Pedestrian Detection in Severe Lighting Conditions: Comparative Study of Human Performance vs Thermal-Imaging-Based Automatic System
Authors: Nowosielski, A., Małecki, K., Forczmański, P., Smoliński, A.
Published in: Progress in Computer Recognition Systems, Springer, 2020, pp. 174-183
This paper discusses the problem of detecting human bodies in severe lighting conditions from the driver’s perspective. It presents the results of a study on threat situation recognition, defined as the sudden appearance of a pedestrian in the driver’s field of view. The efficiency of human reaction and delay time are contrasted with an automatic detection system based on thermal imagery.
@InProceedings{Nowosielski2020_comparative, author = {Nowosielski, Adam and Małecki, Krzysztof and Forczmański, Paweł and Smoliński, Anton}, title = {Pedestrian Detection in Severe Lighting Conditions: Comparative Study of Human Performance vs Thermal-Imaging-Based Automatic System}, booktitle = {Progress in Computer Recognition Systems}, year = {2020}, publisher = {Springer International Publishing}, pages = {174--183}, doi = {10.1007/978-3-030-19738-4_18},}Nowosielski, A., Małecki, K., Forczmański, P., & Smoliński, A. (2020). Pedestrian Detection in Severe Lighting Conditions: Comparative Study of Human Performance vs Thermal-Imaging-Based Automatic System. In _Progress in Computer Recognition Systems_ (pp. 174-183). Springer International Publishing.Nowosielski, Adam, et al. "Pedestrian Detection in Severe Lighting Conditions: Comparative Study of Human Performance vs Thermal-Imaging-Based Automatic System." _Progress in Computer Recognition Systems_, Springer International Publishing, 2020, pp. 174-183.