K
Kunio Fukunaga
Researcher at Osaka Prefecture University
Publications - 65
Citations - 743
Kunio Fukunaga is an academic researcher from Osaka Prefecture University. The author has contributed to research in topics: 3D single-object recognition & Cognitive neuroscience of visual object recognition. The author has an hindex of 11, co-authored 65 publications receiving 666 citations. Previous affiliations of Kunio Fukunaga include Kwansei Gakuin University.
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Journal ArticleDOI
Natural Language Description of Human Activities from Video Images Based on Concept Hierarchy of Actions
TL;DR: A method for describing human activities from video images based on concept hierarchies of actions based on semantic primitives, which demonstrates the performance of the proposed method by several experiments.
Proceedings ArticleDOI
Generating natural language description of human behavior from video images
TL;DR: This work proposes an approach to generating a natural language description of human behavior appearing in real video images using a model based method and a technique of machine translation.
Proceedings ArticleDOI
Blackboard segmentation using video image of lecture and its applications
TL;DR: This work proposes a method for segmentation of written regions on a blackboard in the lecture room using a video image, which first detects the static edges of which locations on the image are stationary, and extracts several rectangular regions in which these static edges are located densely.
Journal ArticleDOI
Detection of a Solitude Senior's Irregular States Based on Learning and Recognizing of Behavioral Patterns
TL;DR: In this article, a monitoring system focused on behavioral patterns of a solitude senior is proposed, which can detect irregular patterns by the degree of likelihood in the case when non-daily behavioral patterns appeared.
Journal ArticleDOI
Learning and recognizing behavioral patterns using position and posture of human body and its application to detection of irregular states
TL;DR: This paper proposes the following technique, and in experiments, human motions and behavioral patterns in an indoor environment were learned and recognized, and the effectiveness of the method was demonstrated.