Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
Detecting Irregularities in Images and in Video
International Journal of Computer Vision
Object detection by global contour shape
Pattern Recognition
Evaluation of GIST descriptors for web-scale image search
Proceedings of the ACM International Conference on Image and Video Retrieval
New trends and ideas in visual concept detection: the MIR flickr retrieval evaluation initiative
Proceedings of the international conference on Multimedia information retrieval
Indexing in large scale image collections: Scaling properties and benchmark
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Data-driven visual similarity for cross-domain image matching
Proceedings of the 2011 SIGGRAPH Asia Conference
Image retrieval with geometry-preserving visual phrases
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Fast organization of large photo collections using CUDA
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
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Due to high interest of social online systems, there exists a huge and still increasing amount of image data in the web. In order to handle this massive amount of visual information, algorithms often need to be redesigned. In this work, we developed an efficient approach to find visual similarities between images that runs completely on GPU and is applicable to large image databases. Based on local self-similarity descriptors, the approach finds similarities even across modalities. Given a set of images, a database is created by storing all descriptors in an arrangement suitable for parallel GPU-based comparison. A novel voting-scheme further considers the spatial layout of descriptors with hardly any overhead. Thousands of images are searched in only a few seconds. We apply our algorithm to cluster a set of image responses to identify various senses of ambiguous words and re-tag similar images with missing tags.