Scipediacontent: Scipediacontent moved page Draft Content 915597625 to Colomb et al 2016a

2021-02-03T19:26:25Z

Scipediacontent moved page Draft Content 915597625 to Colomb et al 2016a

Scipediacontent: Created page with " == Abstract == Nowadays, many pedestrians are victims of road accidents. Several artificial vision solutions, based on pedestrian detection, have therefore been developed to..."

2021-02-03T19:26:21Z

Created page with " == Abstract == Nowadays, many pedestrians are victims of road accidents. Several artificial vision solutions, based on pedestrian detection, have therefore been developed to..."

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== Abstract ==

Nowadays, many pedestrians are victims of road accidents. Several artificial vision solutions, based on pedestrian detection, have therefore been developed to assist drivers and reduce the accident rate. But most of the proposed pedestrian databases make it possible to test detection only in favorable conditions. The main goal of this research is to provide a learning and testing environment for the development of pedestrian detectors able to function under all weather conditions by day and even by night. This paper presents a new database, called Cerema, composed of 10 sets which include normal and degraded conditions (day, night, fog, rain). Image data will include detailed annotations for each set. Two common detectors are used to show the usefulness of our database, which are HOG and Haar. Finally, the results obtained on this new database will be presented to show the impact of adverse weather conditions on these two different detectors.

== Original document ==

The different versions of the original document can be found in:

* [https://hal.archives-ouvertes.fr/hal-02121683 https://hal.archives-ouvertes.fr/hal-02121683]

* [http://xplorestaging.ieee.org/ielx7/7936636/7939824/07939916.pdf?arnumber=7939916 http://xplorestaging.ieee.org/ielx7/7936636/7939824/07939916.pdf?arnumber=7939916],
: [http://dx.doi.org/10.1109/setit.2016.7939916 http://dx.doi.org/10.1109/setit.2016.7939916]

* [http://xplorestaging.ieee.org/ielx7/8007434/8012058/08012150.pdf?arnumber=8012150 http://xplorestaging.ieee.org/ielx7/8007434/8012058/08012150.pdf?arnumber=8012150],
: [http://dx.doi.org/10.1109/dt.2017.8012150 http://dx.doi.org/10.1109/dt.2017.8012150]

* [http://xplorestaging.ieee.org/ielx7/8007434/8012058/08012150.pdf?arnumber=8012150 http://xplorestaging.ieee.org/ielx7/8007434/8012058/08012150.pdf?arnumber=8012150],
: [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=8012150 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=8012150],
: [https://academic.microsoft.com/#/detail/2748892412 https://academic.microsoft.com/#/detail/2748892412]

* [https://hal.archives-ouvertes.fr/hal-02193554 https://hal.archives-ouvertes.fr/hal-02193554],
: [https://academic.microsoft.com/#/detail/2623901301 https://academic.microsoft.com/#/detail/2623901301]

DOIS: 10.1109/setit.2016.7939916 10.1109/dt.2017.8012150

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Colomb et al 2016a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 915597625 to Colomb et al 2016a

Scipediacontent: Created page with " == Abstract == Nowadays, many pedestrians are victims of road accidents. Several artificial vision solutions, based on pedestrian detection, have therefore been developed to..."