ISRI > Project > Automatic Evidence Selection and Collection

  

Automatic Evidence Selection and Collection

Leader: Seungmin Beak
Contact: Seungmin Beak (smb@skku.edu)


Mailing address:
SungKyunKwan University
Intelligent System Research Center (ISRC)
Nano and Intelligent System Lab
83654 2nd Research building
300 Cheoncheon-dong, Jangan-gu,
Suwon, Gyeonggi-do
440 - 746
Korea
 
Project Description
 

We are developing novel evidence selection & collection method based on Bayesian theorem for object recognition and pose estimation in real environment. Herein the evidence means features such as SIFT (Scale Invariant Feature Transform), line, color, robot motion and so on, for recognition or pose estimation of 3D object. The main advantage of this approach is to estimate probability more easily using Bayesian rule and to select an optimal set of evidences automatically. Therefore this strategy is able to help the robot take advantage of evidence selection automatically in real environment. And we expect that this strategy can apply to some other systems which are necessary for robust object or human recognition.

 * Cognitive Perception Engine (CPE)



* Automatic Evidence Selection



* Experimental Results





 
Personnel
 
 NameTitleEmail Address
 Seungmin BeakResearch Professorsmb@skku.edu
 Jangwon LeeMaster Degreejwlee31@ece.skku.ac.kr
 Changhyun ChoiUndergraduate Studentheanylab@gmail.com
 
Recent publications
 
  • Dependable 3D Recognition and Modeling for Visually Guided Robotic Manipulation and Navigation
  • Sukhan Lee, Jeihun Lee, Seungmin Beak, Dongju Moon and Woong-Myung Kim
    The 5th IARP-IEEE/RAS-EURON Workshop on Technical Challenges for Dependable Robots in Human Environments (IARP07), 2007

    [Download : pdf]



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    300 Cheoncheon-dong, jangan-gu, Suwon, Gyeonggi-do, 440-746, Korea

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