CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Landmark image classification using 3D point clouds
Xiao, Xian; Xu, Changsheng; Wang, Jinqiao
Conference NameMM'10 - the ACM Multimedia 2010 International Conference
Source PublicationACM Multimedia Conferenc (MM)
Conference Date2010
Conference PlaceChicago, IL, USA
AbstractMost of the existing approaches for landmark image classification
utilize either holistic features or interest of points in the whole
image to train the classification model, which may lead to
unsatisfactory result due to involvement of much information nonlocated
on the landmark in the training process. In this paper, we
propose a novel approach to improve landmark image classification
result via a process of 2D to 3D reconstruction and 3D to 2D
projection of iconic landmark images. Particularly, we first select
iconic images from labeled landmark image collections to
reconstruct a 3D landmark represented in point clouds. Then, 3D
point clouds are projected back onto the same iconic images to
obtain the landmark-region of each iconic image and subsequently
extract SIFT features from the landmark-region to construct a kdimensional
tree (kd-tree) for each landmark. This process is able to
filter out noise points corresponding to clutter background and nonlandmark
objects in the iconic images. Finally, the unlabeled images
can be classified into predefined landmark categories based on the
amount of matched feature points between the image features and
the kd-trees. The experimental result and comparison with the stateof-
the-art demonstrate the effectiveness of our approach.
KeywordLandmark Image 3d Point Clouds
Indexed ByEI
Document Type会议论文
Corresponding AuthorWang, Jinqiao
Recommended Citation
GB/T 7714
Xiao, Xian,Xu, Changsheng,Wang, Jinqiao. Landmark image classification using 3D point clouds[C],2010:719-722.
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