Ambient Visualization in the Big Data Era -Abstract Hierarchy Browsing of Semi-Structured Imagery Data

2014 Fiscal Year Final Research Report

• Project/Area Number: 25540045
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: High performance computing
• Research Institution: Keio University
• Principal Investigator: FUJISHIRO Issei 慶應義塾大学, 理工学部, 教授 (00181347)
• Co-Investigator(Kenkyū-buntansha): MAO Xiaoyang 山梨大学, 総合研究部, 教授 (20283195)
• Project Period (FY): 2013-04-01 – 2015-03-31
• Keywords: 環境可視化 / ビッグデータ / 半構造映像データ / 抽象化階層 / 人称変換 / 深度付カメラ / 裸眼立体視 / 情動

Outline of Final Research Achievements

In this study, a rapid prototyping was conducted to develop an ambient visualization system towards the big data era. We focused our attention to semi-structured information embedded in a set of imagery datasets produced routinely, to convert its abstraction hierarchy to the corresponding nested layered graph. Then we employed a depth camera to keep track of the gaze and gesture of a viewer to detect changes in his/her affect in an unconscious way, in order to make it possible to adaptively transform his/her person view through the up-and-down movement over the layers in the abstraction hierarchy. By taking full advantage of this hierarchical browsing together with simple naked-eye stereovision functions, a strong support can be provided for audience in front of digital signage or through SNS to comprehend a given universe of discourse wholly for subsequent prompt and effective actions.

Free Research Field

ビジュアルコンピューティング