| Project/Area Number |
11680404
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Osaka Electro-Communication University |
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Principal Investigator |
HILD Michael Osaka Electro-Communication Univ. Fac. Of Information Scinence and Arts, Lecturer, 総合情報学部, 講師 (30268297)
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| Co-Investigator(Kenkyū-buntansha) |
UMEDA Michio Oska Electro-Communication Univ., Fac. Of Information Scinece and Arts, Professor, 総合情報学部, 教授 (30213490)
SHIRAI Yoshiaki Osaka University, Graduate School of Engineering, Professor, 大学院・工学研究科, 教授 (50206273)
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| Project Period (FY) |
1999 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,000,000 (Direct Cost: ¥3,000,000)
Fiscal Year 2001: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2000: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 1999: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | object recognition / learning / human actions / シーンの認識 / 画像解析 / 人間の動作 |
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| Research Abstract |
The goal of this research is the development of improved vision-based object recognition methods for indoor scenes. Our research has focused on the following five major topics :
(a) Recognition of indoor scene objects from color image sequences using human actions as a primary cue. We developed a system that first recognizes persons' actions ocurring in the scene and then, based on these, recognizes the objects which are manipulated by these persons
(b) Recognition of indoor objects based on finger-pointing actions. Finger-pointing actions are detected and used to determine objects in the scene
(c) Identification of persons based on human faces in unconstrained indoor environments. Development of a flexible face recognition system, based on a neural network bank
(d) Recognition methods for autonomous driving of wheelchairs in outdoor environments
(e) Fundamental techniques needed for improving sensor singnals and low-level data measurements in the context of the recognition problem
i. Rotational imaging for the reconstruction of 3-D data points of scenes
ii. Background-frame differencing methods based on color similarity
iii. Low-noise image acquistion using contemporary image sensor technology
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