Denis PELLERIN
Professeur UGA
Equipe Architecture, Géométrie, Perception, Images, Gestes
Département Images et Signal
ME CONTACTER / CONTACT ME
Mail : denis.pellerin@gipsa-lab.grenoble-inp.fr

11 rue des mathématiques
Domaine Universitaire
BP 46
38402 Saint Martin d'Hères cedex

Bureau D1116
Tél.33 (0)4 76 57 43 69
Fax : 33 (0)4 76 57 47 90
PUBLICATIONS RECENTES / RECENT PUBLICATIONS
Les derniéres publications de la collection Gipsa dans HAL

Improving Hierarchical Image Classification with Merged CNN Architectures

Anuvabh Dutt, Denis Pellerin, Georges Quénot. Improving Hierarchical Image Classification with Merged CNN Architectures. Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing, Jun 2017, Florence, Italy. ACM, pp.31:1--31:7, 2017, CBMI '17. <https://dl.acm.org/authorize?N46628>. <10.1145/3095713.3095745>. <hal-01590664>

Improving Image Classification Using Coarse and Fine Labels

Anuvabh Dutt, Denis Pellerin, Georges Quénot. Improving Image Classification Using Coarse and Fine Labels. Proceedings of the 2017 ACM International Conference on Multimedia Retrieval, Jun 2017, Bucarest, Romania. ACM, pp.438--442, 2017, ICMR '17. <https://dl.acm.org/authorize?N46629>. <10.1145/3078971.3079042>. <hal-01590672>

A Fast Audiovisual Attention Model for Human Detection and Localization on a Companion Robot

Rémi Ratajczak, Denis Pellerin, Quentin Labourey, Catherine Garbay. A Fast Audiovisual Attention Model for Human Detection and Localization on a Companion Robot. The First International Conference on Applications and Systems of Visual Paradigms (VISUAL 2016), Nov 2016, Barcelone, Spain. VISUAL 2016 Proceedings - ThinkMind. <hal-01408740>

Multi-layer Dictionary Learning for Image Classification

Stefen Chan Wai Tim, Michele Rombaut, Denis Pellerin. Multi-layer Dictionary Learning for Image Classification. ACIVS 2016 : Advanced Concepts for Intelligent Vision Systems, Oct 2016, Lecce, Italy. ACIVS 2016, Advanced Concepts for Intelligent Vision Systems, 2016. <hal-01388907>

An Evidential Filter for Indoor Navigation of a Mobile Robot in Dynamic Environment

Quentin Labourey, Olivier Aycard, Denis Pellerin, Michele Rombaut, Catherine Garbay. An Evidential Filter for Indoor Navigation of a Mobile Robot in Dynamic Environment. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Jun 2016, Eindhoven, Netherlands. 2016, <10.1007/978-3-319-40596-4_25>. <hal-01341861>

Learned features versus engineered features for multimedia indexing

Mateusz Budnik, Efrain-Leonardo Gutierrez-Gomez, Bahjat Safadi, Denis Pellerin, Georges Quénot. Learned features versus engineered features for multimedia indexing. Multimedia Tools and Applications, Springer Verlag, 2016, <10.1007/s11042-016-4240-2>. <hal-01479240>

Rejection-based classification for action recognition using a spatio-temporal dictionary

Stefen Chan Wai Tim, Michele Rombaut, Denis Pellerin. Rejection-based classification for action recognition using a spatio-temporal dictionary. 23rd European Signal Processing Conference (EUSIPCO-2015), Sep 2015, Nice, France. <hal-01202028>

Sound classification in indoor environment thanks to belief functionsClassification de sons en environnement intérieur à l'aide de fonctions de croyance

Quentin Labourey, Denis Pellerin, Michele Rombaut, Olivier Aycard, Catherine Garbay. Sound classification in indoor environment thanks to belief functions. 23rd European Signal Processing Conference (EUSIPCO-2015), Aug 2015, Nice, France. <hal-01199193>

does color influence eye movements while exploring videos ?

Shahrbanoo Hamel, Dominique Houzet, Denis Pellerin, Nathalie Guyader. does color influence eye movements while exploring videos ?. Journal of Eye Movement Research, International Group for Eye Movement Research - University of Bern, Switzerland, 2015, 8 (1), pp.1-10. <10.16910/jemr.8.1.4>. <hal-01234898>

Contribution of color in saliency model for videos

Hamel Shahrbanoo, Nathalie Guyader, Denis Pellerin, Dominique Houzet. Contribution of color in saliency model for videos. Signal, Image and Video Processing, Springer Verlag, 2015, pp.1-7. <10.1007/S11760-015-0765-5>. <hal-01137514>

ENCADREMENT DE THESES / PhD THESIS SUPERVISED
Prénom NOM Date d'entrée en thèse Sujet Ecole doctorale
DUTT Anuvabh01/10/2016Incremental Learning for Visual RecognitionMSTII

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal