cvpr cvpr2013 cvpr2013-38 cvpr2013-38-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: unkown-author
Abstract: The objective of this paper is large scale object instance retrieval, given a query image. A starting point of such systems is feature detection and description, for example using SIFT. The focus of this paper, however, is towards very large scale retrieval where, due to storage requirements, very compact image descriptors are required and no information about the original SIFT descriptors can be accessed directly at run time. We start from VLAD, the state-of-the art compact descriptor introduced by J´ egou et al. [8] for this purpose, and make three novel contributions: first, we show that a simple change to the normalization method significantly improves retrieval performance; second, we show that vocabulary adaptation can substantially alleviate problems caused when images are added to the dataset after initial vocabulary learning. These two methods set a new stateof-the-art over all benchmarks investigated here for both mid-dimensional (20k-D to 30k-D) and small (128-D) descriptors. Our third contribution is a multiple spatial VLAD representation, MultiVLAD, that allows the retrieval and local- ization of objects that only extend over a small part of an image (again without requiring use of the original image SIFT descriptors).
[1] R. Arandjelovi c´ and A. Zisserman. Three things everyone should know to improve object retrieval. In Proc. CVPR, 2012.
[2] D. Chen, S. Tsai, V. Chandrasekhar, G. Takacs, H. Chen, R. Vedantham, R. Grzeszczuk, and B. Girod. Residual enhanced visual vectors for on-device image matching. In Asilomar, 2011.
[3] O. Chum, A. Mikulik, M. Perdˇoch, and J. Matas. Total recall II: Query expansion revisited. In Proc. CVPR, 2011.
[4] O. Chum, J. Philbin, J. Sivic, M. Isard, and A. Zisserman. Total recall: Automatic query expansion with a generative feature model for object retrieval. In Proc. ICCV, 2007.
[5] H. J e´gou and O. Chum. Negative evidences and co-occurrences in image retrieval: the benefit of PCA and whitening. In Proc. ECCV, 2012.
[6] H. J ´egou, M. Douze, and C. Schmid. Hamming embedding and weak geometric consistency for large scale image search. In Proc. ECCV, 2008.
[7] H. J ´egou, M. Douze, and C. Schmid. On the burstiness of visual elements. In Proc. CVPR, Jun 2009.
[8] H. J ´egou, M. Douze, C. Schmid, and P. P ´erez. Aggregating local descriptors into a compact image representation. In Proc. CVPR, 2010.
[9] H. J ´egou, F. Perronnin, M. Douze, J. S ´anchez, P. P ´erez, and C. Schmid. Aggregating local images descriptors into compact
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20] codes. IEEE PAMI, 2012. M. Perdˇoch, O. Chum, and J. Matas. Efficient representation of local geometry for large scale object retrieval. In Proc. CVPR, 2009. F. Perronnin and D. Dance. Fisher kernels on visual vocabularies for image categorization. In Proc. CVPR, 2007. F. Perronnin, Y. Liu, J. Sanchez, and H. Poirier. Large-scale image retrieval with compressed fisher vectors. In Proc. CVPR, 2010. J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object retrieval with large vocabularies and fast spatial matching. In Proc. CVPR, 2007. J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Lost in quantization: Improving particular object retrieval in large scale image databases. In Proc. CVPR, 2008. K. Simonyan, A. Vedaldi, and A. Zisserman. Descriptor learning using convex optimisation. In Proc. ECCV, 2012. J. Sivic and A. Zisserman. Video Google: A text retrieval approach to object matching in videos. In Proc. ICCV, 2003. A. Torii, J. Sivic, and T. Pajdla. Visual localization by linear combination of image descriptors. In International Workshop on Mobile Vision, 2011. J. C. van Gemert, J. M. Geusebroek, C. J. Veenman, and A. W. M. Smeulders. Kernel codebooks for scene categorization. In Proc. ECCV, 2008. S. Winder, G. Hua, and M. Brown. Picking the best daisy. In Proc. CVPR, 2009. X. Zhou, K. Yu, T. Zhang, and T. S. Huang. Image classification using super-vector coding of local image descriptors. In Proc. ECCV, 2010. 111555888533