HapticV1, PascalFrancis, Curation, bibRecord, 001157

Perception-aware packet-loss resilient compression for networked haptic systems : Human-Centric Multimedia Networking

Identifieur interne : 001157 ( PascalFrancis/Curation ); précédent : 001156; suivant : 001158

Perception-aware packet-loss resilient compression for networked haptic systems : Human-Centric Multimedia Networking

Auteurs : Jalal Awed [Liban] ; Imad H. Elhajj [Liban] ; Ali Chehab [Liban] ; Ayman Kayssi [Liban]

Source :

Computer communications [ 0140-3664 ] ; 2013.

RBID : Pascal:14-0025581

Descripteurs français

Pascal (Inist)
- Réalité virtuelle, Téléenseignement, Gestion mémoire, Interface utilisateur, Perte transmission, Canal transmission avec perte, Réseau interconnecté, Sensibilité tactile, Perception sensorielle, Prédiction linéaire, Comportement utilisateur, Taux compression, Analyse statistique, Téléopération, Résilience.
Wicri :
- topic : Réalité virtuelle.

English descriptors

KwdEn :
- Compression ratio, Interconnected power system, Linear prediction, Lossy channel, Remote operation, Remote teaching, Resilience, Sensorial perception, Statistical analysis, Storage management, Tactile sensitivity, Transmission loss, User behavior, User interface, Virtual reality.

Abstract

Haptic systems are increasingly being used in various applications such as virtual training, remote presence, and telesurgery. Human perception characteristics play a major role in the design of perceptual compression methods for haptic systems. However, the performance of these methods is jeopardized when packet loss occurs in the network. This study presents a packet loss resilient perceptual compression method, the modified prediction deadband method, as a novel enhancement on the linear prediction deadband method. The proposed method shows a significant improvement in user experience compared to other previously published methods, without a considerable loss in the compression ratio. Moreover, the method presents many advantages over other error-resilient compression methods, since it has a low footprint on the computational cost and on the memory consumption of the system. In addition, it does not require any previous knowledge or statistics regarding the state of the network.

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A11	`03`	`1`		`@1 CHEHAB (Ali)`
A11	`04`	`1`		`@1 KAYSSI (Ayman)`
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C01	`01`		`ENG`	@0 Haptic systems are increasingly being used in various applications such as virtual training, remote presence, and telesurgery. Human perception characteristics play a major role in the design of perceptual compression methods for haptic systems. However, the performance of these methods is jeopardized when packet loss occurs in the network. This study presents a packet loss resilient perceptual compression method, the modified prediction deadband method, as a novel enhancement on the linear prediction deadband method. The proposed method shows a significant improvement in user experience compared to other previously published methods, without a considerable loss in the compression ratio. Moreover, the method presents many advantages over other error-resilient compression methods, since it has a low footprint on the computational cost and on the memory consumption of the system. In addition, it does not require any previous knowledge or statistics regarding the state of the network.
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C03	`01`	`X`	`FRE`	`@0 Réalité virtuelle @5 06`
C03	`01`	`X`	`ENG`	`@0 Virtual reality @5 06`
C03	`01`	`X`	`SPA`	`@0 Realidad virtual @5 06`
C03	`02`	`X`	`FRE`	`@0 Téléenseignement @5 07`
C03	`02`	`X`	`ENG`	`@0 Remote teaching @5 07`
C03	`02`	`X`	`SPA`	`@0 Teleensenanza @5 07`
C03	`03`	`X`	`FRE`	`@0 Gestion mémoire @5 08`
C03	`03`	`X`	`ENG`	`@0 Storage management @5 08`
C03	`03`	`X`	`SPA`	`@0 Gestión memoria @5 08`
C03	`04`	`X`	`FRE`	`@0 Interface utilisateur @5 09`
C03	`04`	`X`	`ENG`	`@0 User interface @5 09`
C03	`04`	`X`	`SPA`	`@0 Interfase usuario @5 09`
C03	`05`	`X`	`FRE`	`@0 Perte transmission @5 18`
C03	`05`	`X`	`ENG`	`@0 Transmission loss @5 18`
C03	`05`	`X`	`SPA`	`@0 Pérdida transmisión @5 18`
C03	`06`	`X`	`FRE`	`@0 Canal transmission avec perte @5 19`
C03	`06`	`X`	`ENG`	`@0 Lossy channel @5 19`
C03	`06`	`X`	`SPA`	`@0 Canal con perdida @5 19`
C03	`07`	`X`	`FRE`	`@0 Réseau interconnecté @5 20`
C03	`07`	`X`	`ENG`	`@0 Interconnected power system @5 20`
C03	`07`	`X`	`SPA`	`@0 Red interconectada @5 20`
C03	`08`	`X`	`FRE`	`@0 Sensibilité tactile @5 21`
C03	`08`	`X`	`ENG`	`@0 Tactile sensitivity @5 21`
C03	`08`	`X`	`SPA`	`@0 Sensibilidad tactil @5 21`
C03	`09`	`X`	`FRE`	`@0 Perception sensorielle @5 22`
C03	`09`	`X`	`ENG`	`@0 Sensorial perception @5 22`
C03	`09`	`X`	`SPA`	`@0 Percepción sensorial @5 22`
C03	`10`	`X`	`FRE`	`@0 Prédiction linéaire @5 23`
C03	`10`	`X`	`ENG`	`@0 Linear prediction @5 23`
C03	`10`	`X`	`SPA`	`@0 Predicción lineal @5 23`
C03	`11`	`X`	`FRE`	`@0 Comportement utilisateur @5 24`
C03	`11`	`X`	`ENG`	`@0 User behavior @5 24`
C03	`11`	`X`	`SPA`	`@0 Comportamiento usuario @5 24`
C03	`12`	`X`	`FRE`	`@0 Taux compression @5 25`
C03	`12`	`X`	`ENG`	`@0 Compression ratio @5 25`
C03	`12`	`X`	`SPA`	`@0 Relación compresión @5 25`
C03	`13`	`X`	`FRE`	`@0 Analyse statistique @5 26`
C03	`13`	`X`	`ENG`	`@0 Statistical analysis @5 26`
C03	`13`	`X`	`SPA`	`@0 Análisis estadístico @5 26`
C03	`14`	`X`	`FRE`	`@0 Téléopération @5 27`
C03	`14`	`X`	`ENG`	`@0 Remote operation @5 27`
C03	`14`	`X`	`SPA`	`@0 Teleacción @5 27`
C03	`15`	`X`	`FRE`	`@0 Résilience @5 28`
C03	`15`	`X`	`ENG`	`@0 Resilience @5 28`
C03	`15`	`X`	`SPA`	`@0 Resiliencia @5 28`
N21				`@1 027`
N44	`01`			`@1 OTO`
N82				`@1 OTO`

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Pascal:14-0025581

Le document en format XML

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<front><div type="abstract" xml:lang="en">Haptic systems are increasingly being used in various applications such as virtual training, remote presence, and telesurgery. Human perception characteristics play a major role in the design of perceptual compression methods for haptic systems. However, the performance of these methods is jeopardized when packet loss occurs in the network. This study presents a packet loss resilient perceptual compression method, the modified prediction deadband method, as a novel enhancement on the linear prediction deadband method. The proposed method shows a significant improvement in user experience compared to other previously published methods, without a considerable loss in the compression ratio. Moreover, the method presents many advantages over other error-resilient compression methods, since it has a low footprint on the computational cost and on the memory consumption of the system. In addition, it does not require any previous knowledge or statistics regarding the state of the network.</div>
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<fC01 i1="01" l="ENG"><s0>Haptic systems are increasingly being used in various applications such as virtual training, remote presence, and telesurgery. Human perception characteristics play a major role in the design of perceptual compression methods for haptic systems. However, the performance of these methods is jeopardized when packet loss occurs in the network. This study presents a packet loss resilient perceptual compression method, the modified prediction deadband method, as a novel enhancement on the linear prediction deadband method. The proposed method shows a significant improvement in user experience compared to other previously published methods, without a considerable loss in the compression ratio. Moreover, the method presents many advantages over other error-resilient compression methods, since it has a low footprint on the computational cost and on the memory consumption of the system. In addition, it does not require any previous knowledge or statistics regarding the state of the network.</s0>
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<s5>06</s5>
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<fC03 i1="01" i2="X" l="ENG"><s0>Virtual reality</s0>
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<fC03 i1="01" i2="X" l="SPA"><s0>Realidad virtual</s0>
<s5>06</s5>
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<fC03 i1="03" i2="X" l="ENG"><s0>Storage management</s0>
<s5>08</s5>
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<fC03 i1="03" i2="X" l="SPA"><s0>Gestión memoria</s0>
<s5>08</s5>
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<fC03 i1="04" i2="X" l="FRE"><s0>Interface utilisateur</s0>
<s5>09</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>User interface</s0>
<s5>09</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Interfase usuario</s0>
<s5>09</s5>
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<fC03 i1="05" i2="X" l="FRE"><s0>Perte transmission</s0>
<s5>18</s5>
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<fC03 i1="05" i2="X" l="ENG"><s0>Transmission loss</s0>
<s5>18</s5>
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<fC03 i1="05" i2="X" l="SPA"><s0>Pérdida transmisión</s0>
<s5>18</s5>
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<fC03 i1="06" i2="X" l="FRE"><s0>Canal transmission avec perte</s0>
<s5>19</s5>
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<s5>19</s5>
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<fC03 i1="06" i2="X" l="SPA"><s0>Canal con perdida</s0>
<s5>19</s5>
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<s5>21</s5>
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<s5>21</s5>
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<s5>22</s5>
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<fC03 i1="09" i2="X" l="ENG"><s0>Sensorial perception</s0>
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<s5>23</s5>
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<fC03 i1="11" i2="X" l="FRE"><s0>Comportement utilisateur</s0>
<s5>24</s5>
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<fC03 i1="11" i2="X" l="ENG"><s0>User behavior</s0>
<s5>24</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Comportamiento usuario</s0>
<s5>24</s5>
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<fC03 i1="12" i2="X" l="FRE"><s0>Taux compression</s0>
<s5>25</s5>
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<fC03 i1="12" i2="X" l="ENG"><s0>Compression ratio</s0>
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   |wiki=    Ticri/CIDE
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   |clé=     Pascal:14-0025581
   |texte=   Perception-aware packet-loss resilient compression for networked haptic systems : Human-Centric Multimedia Networking
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Perception-aware packet-loss resilient compression for networked haptic systems : Human-Centric Multimedia Networking

Perception-aware packet-loss resilient compression for networked haptic systems : Human-Centric Multimedia Networking

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