Title
Image-Searching For Office Equipment Using Bag-Of-Keypoints And Adaboost
Abstract
For an indoor mobile robot's Simultaneous Localization And Mapping (SLAM), a method of processing only one monocular image (640 x 480 pixel) of the environment is proposed. This method imitates a human's ability to grasp at a glance the overall situation of a room, i.e., its layout and any objects or obstacles in it. Specific object recognition of a desk through the use of several camera angles is dealt with as one example. The proposed method has the following steps. 1) The bag-of-keypoints method is applied to the image to detect the existence of the object in the input image. 2) If the existence of the object is verified, the angle of the object is further detected using the bag-of-keypoints method. 3) The candidates for the projection from template image to input image are obtained using Scale Invariant Feature Transform (SIFT) or edge information. Whether or not the projected area correctly corresponds to the object is checked using the AdaBoost classifier, based on various image features such as Haar-like features. Through these steps, the desk is eventually extracted with angle information if it exists in the image.
Year
DOI
Venue
2011
10.20965/jrm.2011.p1080
JOURNAL OF ROBOTICS AND MECHATRONICS
Keywords
Field
DocType
bag-of-keypoints, SIFT, AdaBoost, specific object recognition
Computer vision,Scale-invariant feature transform,AdaBoost,Pattern recognition,Computer science,Artificial intelligence
Journal
Volume
Issue
ISSN
23
6
0915-3942
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Seiji Aoyagi12514.63
Atsushi Kohama200.68
Yuki Inaura300.34
Masato Suzuki427.57
Tomokazu Takahashi5322100.16