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3 results on '"Technicolor"'

1. Continuous Arousal Self-assessments Validation Using Real-time Physiological Responses

Author

Christel Chamaret, Ting Li, Emmanuel Dellandréa, Liming Chen, Yoann Baveye, Technicolor R & I [Cesson Sévigné], Technicolor, Extraction de Caractéristiques et Identification (imagine), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), and ANR-12-CHRI-0002,ViSen,Annotation de données visuelles avec des descriptions sémantiques(2012)

Subjects
Temporal correlation, Experimental validation, Galvanic skin response, Computer science, Speech recognition, 05 social sciences, [INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM], Affective computing, 02 engineering and technology, Affect (psychology), 050105 experimental psychology, Physiological responses, Arousal, Arousal self-assessment, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, 0501 psychology and cognitive sciences, Skin conductance
Abstract

International audience; On one hand, the fact that Galvanic Skin Response (GSR) is highly correlated with the user affective arousal provides the possibility to apply GSR in emotion detection. On the other hand, temporal correlation of real-time GSR and self-assessment of arousal has not been well studied. This paper confronts two modalities representing the induced emotion when watching 30 movies extracted from the LIRIS-ACCEDE database. While continuous arousal annotations have been self-assessed by 5 participants using a joystick, real-time GSR signal of 13 other subjects is supposed to catch user emotional response, objectively without user's interpretation. As a main contribution, this paper introduces a method to make possible the temporal comparison of both signals. Thus, temporal correlation between continuous arousal peaks and GSR were calculated for all 30 movies. A global Pearson's correlation of 0.264 and a Spearman's rank correlation coefficient of 0.336 were achieved. This result proves the validity of using both signals to measure arousal and draws a reliable framework for the analysis of such signals.

Published
2015
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2. Bipartite graph structures for efficient balancing of heterogeneous loads

Author

LelargeMarc, LeconteMathieu, MassouliéLaurent, Laboratory of Information, Network and Communication Sciences (LINCS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT), Technicolor Paris lab, Technicolor, Dynamics of Geometric Networks (DYOGENE), Département d'informatique de l'École normale supérieure (DI-ENS), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire d'informatique de l'école normale supérieure (LIENS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Microsoft Research - Inria Joint Centre (MSR - INRIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Microsoft Research Laboratory Cambridge-Microsoft Corporation [Redmond, Wash.], Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Inria Paris-Rocquencourt, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)

Subjects
Service (systems architecture), Matching (statistics), Optimal matching, Scale (ratio), Computer Networks and Communications, Computer science, Matchings, Distributed computing, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], 0211 other engineering and technologies, Scale (descriptive set theory), 02 engineering and technology, 01 natural sciences, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], 010104 statistics & probability, Random Graphs, Server, C.2.4 [Computer-Communication Networks]: Distributed Systems, Bandwidth (computing), 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Random graph, 021103 operations research, 020206 networking & telecommunications, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Hardware and Architecture, Feature (computer vision), Bipartite graph, Software, Content Delivery Networks, Content Placement Policies
Abstract

This paper considers large scale distributed content service platforms, such as peer-to-peer video-on-demand systems. Such systems feature two basic resources, namely storage and bandwidth. Their efficiency critically depends on two factors: (i) content replication within servers, and (ii) how incoming service requests are matched to servers holding requested content. To inform the corresponding design choices, we make the following contributions. We first show that, for underloaded systems, so-called proportional content placement with a simple greedy strategy for matching requests to servers ensures full system efficiency provided storage size grows logarithmically with the system size. However, for constant storage size, this strategy undergoes a phase transition with severe loss of efficiency as system load approaches criticality. To better understand the role of the matching strategy in this performance degradation, we characterize the asymptotic system efficiency under an optimal matching policy. Our analysis shows that -in contrast to greedy matching- optimal matching incurs an inefficiency that is exponentially small in the server storage size, even at critical system loads. It further allows a characterization of content replication policies that minimize the inefficiency. These optimal policies, which differ markedly from proportional placement, have a simple structure which makes them implementable in practice. On the methodological side, our analysis of matching performance uses the theory of local weak limits of random graphs, and highlights a novel characterization of matching numbers in bipartite graphs, which may both be of independent interest.

Published
2012
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3. Uncovering Influence Cookbooks

Author

Erwan Le Merrer, Gilles Trédan, Technicolor, Équipe Tolérance aux fautes et Sûreté de Fonctionnement informatique (LAAS-TSF), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)

Subjects
FOS: Computer and information sciences, Reverse engineering, Exploit, Computer science, media_common.quotation_subject, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], 02 engineering and technology, Topology, computer.software_genre, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], Ranking (information retrieval), 020204 information systems, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Function (engineering), media_common, Social and Information Networks (cs.SI), Service (business), Social network, business.industry, 05 social sciences, Rank (computer programming), Computer Science - Social and Information Networks, Metric (mathematics), business, computer, 050203 business & management
Abstract

Ensuring the early detection of important social network users is a challenging task. Some peer ranking services are now well established, such as PeerIndex, Klout, or Kred. Their function is to rank users according to their influence. This notion of influence is however abstract, and the algorithms achieving this ranking are opaque. Following the rising demand for a more transparent web, we explore the problem of gaining knowledge by reverse engineering such peer ranking services, with regards to the social network topology they get as an input. Since these services exploit the online activity of users (and therefore their connectivity in social networks), we provide a precise evaluation of how topological metrics of the social network impact the final user ranking. Our approach is the following : we first model the ranking service as a black-box with which we interact by creating user profiles and by performing operations on them. Through those profiles, we trigger some slight topological modifications. By monitoring the impact of these modifications on the rankings of those profiles, we infer the weight of each topological metric in the black-box, thus reversing the service influence cookbook., Comment: To appear in CSCW 2017 (The 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing)

Published
2017
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