Framework of image understanding based on PDP model-proposition of ICE(image CEntered) system

Naoyuki Tsuruta; Takuma Akagi; Rin ichiro Taniguchi; Makoto Amamiya

Framework of image understanding based on PDP model-proposition of ICE(image CEntered) system

Naoyuki Tsuruta, Takuma Akagi, Rin ichiro Taniguchi, Makoto Amamiya

Real world robotics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

One of the most important tasks in image understanding is to map visual information into symbolic concepts which describe an input scene. However, the mapping presents the following difficulties: 1. How to resolve the ambiguity in visual information. 2. How to reduce the redundancy of visual information. 3. How to describe scenes efficiently using symbolic concepts. In this paper, we propose the ICE System, which is a framework of computer vision addressing the above three problems. First we will see a multi-layered model based on the hypercolumn with selective attention mechanism can solve the first two problems. Then, we will describe how the ICE System is structurally constructed on the basis of the multi-layered model.

Original language	English
Title of host publication	Proceedings of the International Joint Conference on Neural Networks
Publisher	Publ by IEEE
Pages	177-180
Number of pages	4
ISBN (Print)	0780314212, 9780780314214
Publication status	Published - 1993
Event	Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn Duration: Oct 25 1993 → Oct 29 1993

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	1

Other

Other	Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
City	Nagoya, Jpn
Period	10/25/93 → 10/29/93

All Science Journal Classification (ASJC) codes

Software
Artificial Intelligence

Cite this

Framework of image understanding based on PDP model-proposition of ICE(image CEntered) system. / Tsuruta, Naoyuki; Akagi, Takuma; Taniguchi, Rin ichiro et al.

Proceedings of the International Joint Conference on Neural Networks. Publ by IEEE, 1993. p. 177-180 (Proceedings of the International Joint Conference on Neural Networks; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tsuruta, N, Akagi, T, Taniguchi, RI & Amamiya, M 1993, Framework of image understanding based on PDP model-proposition of ICE(image CEntered) system. in Proceedings of the International Joint Conference on Neural Networks. Proceedings of the International Joint Conference on Neural Networks, vol. 1, Publ by IEEE, pp. 177-180, Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3), Nagoya, Jpn, 10/25/93.

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abstract = "One of the most important tasks in image understanding is to map visual information into symbolic concepts which describe an input scene. However, the mapping presents the following difficulties: 1. How to resolve the ambiguity in visual information. 2. How to reduce the redundancy of visual information. 3. How to describe scenes efficiently using symbolic concepts. In this paper, we propose the ICE System, which is a framework of computer vision addressing the above three problems. First we will see a multi-layered model based on the hypercolumn with selective attention mechanism can solve the first two problems. Then, we will describe how the ICE System is structurally constructed on the basis of the multi-layered model.",

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AB - One of the most important tasks in image understanding is to map visual information into symbolic concepts which describe an input scene. However, the mapping presents the following difficulties: 1. How to resolve the ambiguity in visual information. 2. How to reduce the redundancy of visual information. 3. How to describe scenes efficiently using symbolic concepts. In this paper, we propose the ICE System, which is a framework of computer vision addressing the above three problems. First we will see a multi-layered model based on the hypercolumn with selective attention mechanism can solve the first two problems. Then, we will describe how the ICE System is structurally constructed on the basis of the multi-layered model.

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BT - Proceedings of the International Joint Conference on Neural Networks

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ER -

Framework of image understanding based on PDP model-proposition of ICE(image CEntered) system

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