3D Object Recognition Using Appearance Model Space of Feature Point


KIPS Transactions on Software and Data Engineering, Vol. 3, No. 2, pp. 93-100, Feb. 2014
10.3745/KTSDE.2014.3.2.93,   PDF Download:

Abstract

3D object recognition using only 2D images is a difficult work because each images are generated different to according to the view direction of cameras. Because SIFT algorithm defines the local features of the projected images, recognition result is particularly limited in case of input images with strong perspective transformation. In this paper, we propose the object recognition method that improves SIFT algorithm by using several sequential images captured from rotating 3D object around a rotation axis. We use the geometric relationship between adjacent images and merge several images into a generated feature space during recognizing object. To clarify effectiveness of the proposed algorithm, we keep constantly the camera position and illumination conditions. This method can recognize the appearance of 3D objects that previous approach can not recognize with usually SIFT algorithm.


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Cite this article
[IEEE Style]
S. M. Joo and C. W. Lee, "3D Object Recognition Using Appearance Model Space of Feature Point," KIPS Transactions on Software and Data Engineering, vol. 3, no. 2, pp. 93-100, 2014. DOI: 10.3745/KTSDE.2014.3.2.93.

[ACM Style]
Seong Moon Joo and Chil Woo Lee. 2014. 3D Object Recognition Using Appearance Model Space of Feature Point. KIPS Transactions on Software and Data Engineering, 3, 2, (2014), 93-100. DOI: 10.3745/KTSDE.2014.3.2.93.