1994 Fiscal Year Final Research Report Summary
Space Recognition as Visual Information Processing by Means of Hypothetical Reasoning
| Project/Area Number |
05452358
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Osaka University |
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Principal Investigator |
KITAHASHI Tadahiro Osaka University・I.S.I.R., Professor, 産業科学研究所, 教授 (70029453)
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| Co-Investigator(Kenkyū-buntansha) |
GU Haisong Osaka University・I.S.I.R., Research Associate, 産業科学研究所, 助手 (80263317)
KAKUSHO Koh Osaka University・I.S.I.R., Research Associate, 産業科学研究所, 助手 (50263322)
DAN Seiichiro Kinki University・Faculty of Science & Engineering, Assiatant Professor, 理工学部, 講師 (00207276)
BABAGUCHI Noboru Osaka University・I.S.I.R., Associate Professor, 産業科学研究所, 助教授 (30156541)
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| Project Period (FY) |
1993 – 1994
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| Keywords | Hypothesis-Based Reasoning / Shape Recovery / Inference on Invisible Surface / Scene Reconstruction / Active Vision / Visual Servo / Action Understnading / Salient Frame Extraction |
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| Research Abstract |
(1) Formulation of Hypothetical Reasoning for Visula Information Processing (1993)
We have proposed hypothetical reasoning to recover the three dimensional (3D) shape of an object from its monocular image. In more detail, we have implemented the scheme of relaxational optimization on an EWS by means of the process of choosing hypotheses on the object's 3D shape and verifying them by the shape recovered under the hypotheses.
(2) Acquiring the Description of an Object by Hypothesization and Verificaion (1993)
As extension of the method proposed in (1), we have worked on inferring an object's surface that is invisible in the current view. The inference employs hypotheses on the topological structure of an object's shape together with those on the object's geometric 3D shape. We have also studied recovering the arrangement of objects in the 3D space based on hypotheses on the relative positions among the objects and the position of the floor.
(3) Sensing Strategy to Acquire the Spatial Information of an Object's Shape (1994)
We have developed a method of planning viewpoints for additional sensing to verify the objects' invisible surface inferred by the method proposed in (2). In order for a robot to reach the planned viewpoint, we employed visual servo to correct the robot's current configuration on the sensory data.
(4) Understanding the Actions of Moving Objects (1993-1994)
Toward understanding humans' coordinated actions, we have presented a method to recognize the action patterns from a sequence of images by employing the knowledge of cooperativeness and continuity in actions as a kind of hypotheses. We have also developed a method to extract image frames with salient features to describe the action concisely from an image sequence in the process of the action understanding.
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