Azrour, S., Pierard, S., Geurts, P., & Van Droogenbroeck, M. (2017). A two-step methodology for human pose estimation increasing the accuracy and reducing the amount of learning samples dramatically. In Advanced Concepts for Intelligent Vision Systems (pp. 3-14). Springer. doi:10.1007/978-3-319-70353-4_1 Peer reviewed |
Azrour, S., Pierard, S., & Van Droogenbroeck, M. (2016). Leveraging orientation knowledge to enhance human pose estimation methods. In Articulated Motion and Deformable Objects AMDO 2016 (pp. 81-87). Springer. doi:10.1007/978-3-319-41778-3_8 Peer reviewed |
Azrour, S., Pierard, S., & Van Droogenbroeck, M. (19 May 2016). Improving pose estimation by building dedicated datasets and using orientation [Poster presentation]. Human Motion Analysis for Healthcare Applications, London, United Kingdom. |
Pierard, S., Azrour, S., & Van Droogenbroeck, M. (19 May 2016). Slicing the 3D space into planes for the fast interpretation of human motion [Poster presentation]. Human Motion Analysis for Healthcare Applications, London, United Kingdom. |
Azrour, S., Pierard, S., & Van Droogenbroeck, M. (09 October 2015). Defining a score based on gait analysis for the longitudinal follow-up of MS patients. Multiple Sclerosis Journal, 23 (S11), 408-409. Peer Reviewed verified by ORBi |
Pierard, S., Azrour, S., Phan-Ba, R., DELVAUX, V., Maquet, P., & Van Droogenbroeck, M. (11 September 2014). Diagnosing multiple sclerosis with a gait measuring system, an analysis of the motor fatigue, and machine learning [Paper presentation]. Joint ACTRIMS-ECTRIMS Meeting, Boston, United States. |
Pierard, S., Azrour, S., Phan-Ba, R., & Van Droogenbroeck, M. (17 June 2014). Detection and characterization of gait modifications, for the longitudinal follow-up of patients with neurological diseases, based on the gait analyzing system GAIMS [Poster presentation]. The European Life Sciences Summit BIOMEDICA, Maastricht, Netherlands. |
Pierard, S., Azrour, S., & Van Droogenbroeck, M. (2014). Design of a reliable processing pipeline for the non-intrusive measurement of feet trajectories with lasers. In International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (pp. 4432-4436). doi:10.1109/ICASSP.2014.6854433 Peer reviewed |
Azrour, S., Pierard, S., Geurts, P., & Van Droogenbroeck, M. (2014). Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) (pp. 649-654). Peer reviewed |
Pierard, S., Azrour, S., & Van Droogenbroeck, M. (07 November 2013). Measuring feet trajectories: challenges and applications [Paper presentation]. Workshop on measurement : Challenges and Opportunities, Liège, Belgium. |
Azrour, S., Pierard, S., & Van Droogenbroeck, M. (07 November 2013). Using GAit Measuring System (GAIMS) to discriminate patients with multiple sclerosis from healthy person [Poster presentation]. Workshop on measurement : Challenges and Opportunities, Liège, Belgium. |
Pierard, S., Azrour, S., PHAN BA, R., & Van Droogenbroeck, M. (October 2013). GAIMS: A Reliable Non-Intrusive Gait Measuring System. ERCIM News, 95, 26-27. Peer reviewed |