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1	Automatic Annotation and Segmentation of Sign Language Videos: Base-level Features and Lexical Signs Classification
	Chaaban, Hussein; Gouiffès, Michèle; Braffort, Annelies
	In: 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) ; https://hal.archives-ouvertes.fr/hal-03375858 ; 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021), Feb 2021, Online streaming, France. pp.484-491, ⟨10.5220/0010247104840491⟩ (2021)
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2	Dicta-Sign–LSF–v2 : étendre le traitement automatique des langues des signes grâce à un corpus de dialogue en Langue des Signes
	Belissen, Valentin; Gouiffès, Michèle; Braffort, Annelies
	In: Minority languages spoken or signed and inclusive spaces ; https://hal.archives-ouvertes.fr/hal-03450108 ; Minority languages spoken or signed and inclusive spaces, 2021, Asynchronous online event, France (2021)
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3	Experimenting the Automatic Recognition of Non-Conventionalized Units in Sign Language
	Belissen, Valentin; Braffort, Annelies; Gouiffès, Michèle
	In: ISSN: 1999-4893 ; Algorithms ; https://hal.archives-ouvertes.fr/hal-03060271 ; Algorithms, MDPI, 2020, 13, pp.310-345. ⟨10.3390/a13120310⟩ (2020)
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4	Towards Continuous Recognition of Illustrative and Spatial Structures in Sign Language
	Belissen, Valentin; Braffort, Annelies; Gouiffès, Michèle
	In: ECCV Sign Language Recognition, Translation and Production Workshop ; https://hal.archives-ouvertes.fr/hal-03060270 ; ECCV Sign Language Recognition, Translation and Production Workshop, Springer, Aug 2020, Glasgow, United Kingdom (2020)
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5	MEDIAPI-SKEL -A 2D-Skeleton Video Database of French Sign Language With Aligned French Subtitles
	Bull, Hannah; Braffort, Annelies; Gouiffès, Michèle
	In: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) ; Proceedings of the 12th Language Resources and Evaluation Conference ; 12th Conference on Language Resources and Evaluation (LREC 2020) ; https://hal.archives-ouvertes.fr/hal-02952340 ; 12th Conference on Language Resources and Evaluation (LREC 2020), Jun 2020, Marseille, France. pp.6063-6068 (2020)
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6	Automatic Segmentation of Sign Language into Subtitle-Units
	Bull, Hannah; Gouiffès, Michèle; Braffort, Annelies
	In: Computer Vision – ECCV 2020 Workshops ; Sign Language Recognition, Translation & Production workshop ; https://hal.archives-ouvertes.fr/hal-03098684 ; Sign Language Recognition, Translation & Production workshop, Aug 2020, Glasgow ( virtual ), United Kingdom. ⟨10.1007/978-3-030-66096-3_14⟩ (2020)
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7	Automatic recognition of Sign Language structures in RGB videos: the detection of pointing and lexical signs
	Belissen, Valentin; Gouiffès, Michèle; Braffort, Annelies
	In: https://hal.archives-ouvertes.fr/hal-02146368 ; 2019 (2019)
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8	Optimization of a gesture representation network for Sign Language analysis
	Belissen, Valentin; Gouiffes, Michèle; Braffort, Annelies
	In: https://hal.archives-ouvertes.fr/hal-02146369 ; 2019 (2019)
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9	Towards an Automatic Annotation of French Sign Language Videos: Detection of Lexical Signs
	Chaaban, Hussein; Gouiffès, Michèle; Braffort, Annelies
	In: CAIP 2019: Computer Analysis of Images and Patterns ; https://hal.archives-ouvertes.fr/hal-03058012 ; CAIP 2019: Computer Analysis of Images and Patterns, Sep 2019, Salerno, Italy. pp.402-412, ⟨10.1007/978-3-030-29891-3_35⟩ (2019)
	Abstract: International audience ; This paper presents an approach towards an automatic annotation system for French Sign Language (LSF). Such automation aims to reduce the processing time and the subjectivity of manual annotations done by linguists in order to study the sign language and simplify indexing for automatic signs recognition. The described system uses face and body keypoints collected from 2D RGB standard LSF videos. A naive Bayesian model was built to classify gestural units using the collected keypoints as features. We started from the observation that, for many signers, the production of lexical signs is very often accompanied by mouthing. Effectively, the results showed that the system is capable of detecting lexical signs, with highest success rate, using only information about mouthing and head direction.
	Keyword: [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [INFO]Computer Science [cs]; Annotations; Lexical signs; LSF videos; Mouthing
	URL: https://hal.archives-ouvertes.fr/hal-03058012/document https://hal.archives-ouvertes.fr/hal-03058012/file/Springer_Lecture_Notes_in_Computer_Science__1_.pdf https://doi.org/10.1007/978-3-030-29891-3_35 https://hal.archives-ouvertes.fr/hal-03058012
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10	A Gaussian mixture representation of gesture kinematics for on-line Sign Language video annotation
	Martínez, Fabio; Manzanera, Antoine; Gouiffès, Michèle...
	In: International Symposium on Visual Computing ISVC'15 ; https://hal.archives-ouvertes.fr/hal-01245123 ; International Symposium on Visual Computing ISVC'15, Dec 2015, Las Vegas, United States (2015)
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