Efficient Face Detection Based Crowd Density Estimation using Convolutional Neural Networks and an Improved Sliding Window Strategy

Autor: Kian Ara Rouhollah, Matiolanski Andrzej, Grega Michał, Dziech Andrzej, Baran Remigiusz

Publikováno v: International Journal of Applied Mathematics and Computer Science, Vol 33, Iss 1, Pp 7-20 (2023)

Counting and detecting occluded faces in a crowd is a challenging task in computer vision. In this paper, we propose a new approach to face detection-based crowd estimation under significant occlusion and head posture variations. Most state-of-the-ar

Externí odkaz: https://doaj.org/article/cf2dfbf0c21b4a85a814947f59320039

Impact of the face registration techniques on facial expressions recognition

Autor: José Mennesson, Chabane Djeraba, Ioan Marius Bilasco, Benjamin Allaert

Publikováno v: Signal Processing: Image Communication
Signal Processing: Image Communication, Elsevier, 2018, 61, pp.44-53. ⟨10.1016/j.image.2017.11.002⟩
Signal Processing: Image Communication, 2018, 61, pp.44-53. ⟨10.1016/j.image.2017.11.002⟩

International audience; Recent methodologies for facial expression recognition have been proposed and have obtained good results in near-frontal view. However, these situations do not fairly represent in-the-wild challenges, where expressions are nat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24aaec2c894d6bcefff8c877cf71a497
https://doi.org/10.1016/j.image.2017.11.002

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