Analysis of Thermal Imaging Performance under Extreme Foggy Conditions: Applications to Autonomous Driving

Autor: Josué Manuel Rivera Velázquez, Louahdi Khoudour, Guillaume Saint Pierre, Pierre Duthon, Sébastien Liandrat, Frédéric Bernardin, Sharon Fiss, Igor Ivanov, Raz Peleg

Publikováno v: Journal of Imaging, Vol 8, Iss 11, p 306 (2022)

Object detection is recognized as one of the most critical research areas for the perception of self-driving cars. Current vision systems combine visible imaging, LIDAR, and/or RADAR technology, allowing perception of the vehicle’s surroundings. Ho

Externí odkaz: https://doaj.org/article/b52f28fd6abb4a6da4c9ac6e24915ef8

3D Object Detection with SLS-Fusion Network in Foggy Weather Conditions

Autor: Nguyen Anh Minh Mai, Pierre Duthon, Louahdi Khoudour, Alain Crouzil, Sergio A. Velastin

Publikováno v: Sensors, Vol 21, Iss 20, p 6711 (2021)

The role of sensors such as cameras or LiDAR (Light Detection and Ranging) is crucial for the environmental awareness of self-driving cars. However, the data collected from these sensors are subject to distortions in extreme weather conditions such a

Externí odkaz: https://doaj.org/article/d2dc450694fc4ce6942c0e19f71bfc05

Spatio–Temporal Image Representation of 3D Skeletal Movements for View-Invariant Action Recognition with Deep Convolutional Neural Networks

Autor: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio A. Velastin

Publikováno v: Sensors, Vol 19, Iss 8, p 1932 (2019)

Designing motion representations for 3D human action recognition from skeleton sequences is an important yet challenging task. An effective representation should be robust to noise, invariant to viewpoint changes and result in a good performance with

Externí odkaz: https://doaj.org/article/98b12da522084f13ad7550442e10abec

Sparse LiDAR and Stereo Fusion (SLS-Fusion) for Depth Estimation and 3D Object Detection

Autor: Pierre Duthon, Sergio A. Velastin, Louahdi Khoudour, Nguyen Anh Minh Mai, Alain Crouzil

Publikováno v: 11th International Conference on Pattern Recognition Systems (ICPRS 2021)
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname

Procedings in: 11th International Conference on Pattern Recognition Systems (ICPRS-21), conference paper, 17-19 mar, 2021, Universidad de Talca, Curicó, Chile. The ability to accurately detect and localize objects is recognized as being the most imp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::654d3362f97b163cc426fa737ee9d8ff
https://doi.org/10.1049/icp.2021.1442

A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data

Autor: Sergio A. Velastin, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Houssam Salmane, Huy Hieu Pham

Publikováno v: ICIAR 2019: Image Analysis and Recognition
16th International Conference on Image Analysis and Recognition (ICIAR 2019can)
16th International Conference on Image Analysis and Recognition (ICIAR 2019can), Aug 2019, Waterloo, Canada. pp.18-32, ⟨10.1007/978-3-030-27202-9_2⟩
Lecture Notes in Computer Science ISBN: 9783030272012
ICIAR (1)
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname

We present a new deep learning approach for real-time 3D human action recognition from skeletal data and apply it to develop a vision-based intelligent surveillance system. Given a skeleton sequence, we propose to encode skeleton poses and their moti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5651eedc97a088074cb0c2a18bdc295
https://hal.archives-ouvertes.fr/hal-02883879/document