Viewpoint information

Xavier Bonaventura; Miquel Feixas; Mateu Sbert

Viewpoint information

Xavier Bonaventura
, Miquel Feixas
, Mateu Sbert

Producció científica: Contribució a congrés › Article d'investigació › Avaluat per experts

7 Cites (Scopus)

Resum

In this paper, we present a new perspective to quantify the information associated with a viewpoint. The starting point is twofold: a visibility channel between a set of viewpoints and the polygons of an object, and two specific information measures introduced respectively by DeWeese and Meister (1999) and Butts (2003) to evaluate the significance of stimuli and responses in the neural code. In our approach, these information measures are applied to the visibility channel in order to quantify the information associated with each viewpoint and are compared with both viewpoint entropy and viewpoint mutual information. A number of experiments show the behavior of the proposed measures in best view selection.

Idioma original	Anglès
Pàgines	16-19
Nombre de pàgines	4
Estat de la publicació	Data de publicació - 2011
Esdeveniment	21st International Conference on Computer Graphics and Vision, GraphiCon'2011 - Moscow, Federació Russa Durada: 26 de set. 2011 → 30 de set. 2011

Congrés

Congrés	21st International Conference on Computer Graphics and Vision, GraphiCon'2011
País/Territori	Federació Russa
Ciutat	Moscow
Període	26/09/11 → 30/09/11

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@conference{5539f0a4cf6c45178262de5564117282,

title = "Viewpoint information",

abstract = "In this paper, we present a new perspective to quantify the information associated with a viewpoint. The starting point is twofold: a visibility channel between a set of viewpoints and the polygons of an object, and two specific information measures introduced respectively by DeWeese and Meister (1999) and Butts (2003) to evaluate the significance of stimuli and responses in the neural code. In our approach, these information measures are applied to the visibility channel in order to quantify the information associated with each viewpoint and are compared with both viewpoint entropy and viewpoint mutual information. A number of experiments show the behavior of the proposed measures in best view selection.",

keywords = "Mutual information, Specific information, Viewpoint selection",

author = "Xavier Bonaventura and Miquel Feixas and Mateu Sbert",

year = "2011",

language = "English",

pages = "16--19",

note = "21st International Conference on Computer Graphics and Vision, GraphiCon'2011 ; Conference date: 26-09-2011 Through 30-09-2011",

}

TY - CONF

T1 - Viewpoint information

AU - Bonaventura, Xavier

AU - Feixas, Miquel

AU - Sbert, Mateu

PY - 2011

Y1 - 2011

N2 - In this paper, we present a new perspective to quantify the information associated with a viewpoint. The starting point is twofold: a visibility channel between a set of viewpoints and the polygons of an object, and two specific information measures introduced respectively by DeWeese and Meister (1999) and Butts (2003) to evaluate the significance of stimuli and responses in the neural code. In our approach, these information measures are applied to the visibility channel in order to quantify the information associated with each viewpoint and are compared with both viewpoint entropy and viewpoint mutual information. A number of experiments show the behavior of the proposed measures in best view selection.

AB - In this paper, we present a new perspective to quantify the information associated with a viewpoint. The starting point is twofold: a visibility channel between a set of viewpoints and the polygons of an object, and two specific information measures introduced respectively by DeWeese and Meister (1999) and Butts (2003) to evaluate the significance of stimuli and responses in the neural code. In our approach, these information measures are applied to the visibility channel in order to quantify the information associated with each viewpoint and are compared with both viewpoint entropy and viewpoint mutual information. A number of experiments show the behavior of the proposed measures in best view selection.

KW - Mutual information

KW - Specific information

KW - Viewpoint selection

UR - https://www.scopus.com/pages/publications/84871196206

M3 - Paper

AN - SCOPUS:84871196206

SP - 16

EP - 19

T2 - 21st International Conference on Computer Graphics and Vision, GraphiCon'2011

Y2 - 26 September 2011 through 30 September 2011

ER -

Viewpoint information

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Congrés

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