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AUTOMATIC ANNOTATION OF GEO-INFORMATION IN PANORAMIC STREET VIEW BY IMAGE RETRIEVAL

AUTOMATIC ANNOTATION OF GEO-INFORMATION IN PANORAMIC STREET VIEW BY IMAGE RETRIEVAL. Ming Chen, Yueting Zhuang, Fei Wu College of Computer Science, Zhejiang University. ICIP 2010. Motivation.

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AUTOMATIC ANNOTATION OF GEO-INFORMATION IN PANORAMIC STREET VIEW BY IMAGE RETRIEVAL

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  1. AUTOMATIC ANNOTATION OF GEO-INFORMATION IN PANORAMIC STREET VIEW BY IMAGE RETRIEVAL Ming Chen, Yueting Zhuang, Fei Wu College of Computer Science, Zhejiang University ICIP 2010

  2. Motivation • Recently, some geo-tagged photos have been added into street view as additional illustration images for the same scenes. • But the quality of annotated location is very poor. In this paper, we propose a system to annotate the location tags of users’ images in panoramic street view only with visual features.

  3. System Overview

  4. Coordinate Transformation • A panoramic image is often projected to a spherical surface in order to show users a photo-realistic interactive virtual experience.

  5. Key Points Extraction • We use the conventional method of motion detection to remove the moving regions of foreground. • After the objects are removed, we extracted the key points in all panoramic images using SIFT features, which are invariant to image scale and rotation. • The SIFT descriptors are quantized into visual key words in order to reduce the computational cost of matching.

  6. Image Retrieval • We use hierarchical K-means to obtain visual words from a training set of 20000 images. Locality-sensitive hashing is used to index these visual words. • Given a query image, each bundling feature can be retrieved in the database after they have been extracted. • We can get candidate subset after query images. Then we rank the candidate images by the frequency of its appearance.

  7. Result

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