|  Naaman M, Song Y J, Paepcke A et al. Automatic organization for digital photographs with geographic coordinates. In Proc. the 4th ACM/IEEE Joint Conference on Digital Libraries, June 2004, pp.53–62. Naaman M, Harada S, Wang Y et al. Context data in geo-referenced digital photo collections. In Proc. the 12th ACM International Conference on Multimedia, Oct. 2004, pp.196–203. Cao L, Luo J, Kautz H et al. Annotating collections of photos using hierarchical event and scene models. In Proc. the 21st IEEE Conference on Computer Vision and Pattern Recognition, June 2008. Joshi D, Luo J. Inferring generic activities and events from image content and bags of geo-tags. In Proc. the 7th International Conference on Content-Based Image and Video Retrieval, July 2008, pp.37–46. VianaW, Filho J B, Gensel J et al. PhotoMap —Automatic spatiotemporal annotation for mobile photos. In Proc. the 7th Int. Symp. Web and Wireless Geographical Information Systems, Nov. 2007, pp.187-201. Viana W, Hammiche S, Villanova-Oliver M et al. Photo context as a bag of words. In Proc. the 10th IEEE International Symposium on Multimedia, Dec. 2008, pp.310-315. Crandall D, Felzenszwalb P, Huttenlocher D. Spatial priors for part-based recognition using statistical models. In Proc. the 18th IEEE Conference on Computer Vision and Pattern Recognition, June 2005, pp.10-17. Dalal N, Triggs B. Histograms of oriented gradients for human detection. In Proc. the 18th IEEE Conference on Computer Vision and Pattern Recognition, June 2005, pp.886-893. Felzenszwalb P, McAllester D, Ramanan D. A discriminatively trained, multiscale, deformable part model. In Proc. the 21st IEEE Conference on Computer Vision and Pattern Recognition, June 2008. Felzenszwalb P F, Huttenlocher D P. Pictorial structures for object recognition. International Journal of Computer Vision, 2005, 61(1): 55-79. Hu J, Pei J, Tang J. How can I index my thousands of photos effectively and automatically? An unsupervised feature selection approach. In Proc. the 14th SIAM International Conference on Data Mining, Apr. 2014, pp.136-144. Zhou W, Li H, Lu Y et al. Encoding spatial context for large-scale partial-duplicate web image retrieval. Journal of Computer Science and Technology, 2014, 29(5): 837-848. Shotton J, Winn J, Rother C et al. Textonboost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context. International Journal of Computer Vision, 2009, 81(1): 2-23. Hu S, Chen T, Xu K et al. Internet visual media processing: A survey with graphics and vision applications. The Visual Computer, 2013, 29(5): 393-405. Frome A, Singer Y, Malik J. Image retrieval and classification using local distance functions. In Proc. Neural Information Processing Systems, Dec. 2006, pp.417-424. Russell B C, Torralba A, Liu C et al. Object recognition by scene alignment. In Proc. Neural Information Processing Systems, Dec. 2007, pp.1241-1248. Russell B C, Torralba A, Murphy K P et al. LabelMe: A database and web-based tool for image annotation. International Journal of Computer Vision, 2008, 77(1/2/3): 157-173. Liu C, Yuen J, Torralba A. Nonparametric scene parsing via label transfer. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2368-2382. Liu C, Yuen J, Torralba A. Sift flow: Dense correspondence across different scenes and its applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(5): 978-994. Cao W, Liu N, Kong Q et al. Content-based image retrieval using high-dimensional information geometry. SCIENCE CHINA Information Sciences, 2014, 57(7): 1-11. Gllavata J, Ewerth R, Freisleben B. Text detection in images based on unsupervised classification of high-frequency wavelet coefficients. In Proc. the 17th International Conference on Pattern Recognition, Aug. 2004, pp.425-428. Chen X, Yuille A L. Detecting and reading text in natural scenes. In Proc. the 17th IEEE Conference on Computer Vision and Pattern Recognition, June 2004, pp.366-373. Ye Q, Huang Q, Gao Wet al. Fast and robust text detection in images and video frames. Image and Vision Computing, 2005, 23(6): 565-576. Epshtein B, Ofek E, Wexler Y. Detecting text in natural scenes with stroke width transform. In Proc. the 23rd IEEE Conference on Computer Vision and Pattern Recognition, June 2010, pp.2963-2970. Lee J, Lee P, Lee S et al. AdaBoost for text detection in natural scene. In Proc. the 12th International Conference on Document Analysis and Recognition, Sept. 2011, pp.429-434. Matas J, Chum O, Urban M et al. Robust wide baseline stereo from maximally stable extremal regions. Image and Vision Computing, 2004, 22(10): 761-767. Neumann L, Matas J. Real-time scene text localization and recognition. In Proc. the 25th IEEE Conference on Computer Vision and Pattern Recognition, June 2012, pp.3538-3545. Zhang X, Lin Z, Sun F et al. Transform invariant text extraction. The Visual Computer, 2013, 30(4): 401-415. Chen T, Chen M, Tan P et al. Sketch2Photo: Internet image montage. ACM Transactions on Graphics, 2009, 28(5): Article No. 124. Lee Y, Zitnick C L, Cohen M F. ShadowDraw: Real-time user guidance for freehand drawing. ACM Transactions on Graphics, 2011, 30(4): Article No. 27. Ellis H C. Fundamentals of Human Memory and Cognition (3rd edition). William C. Brown Press, 1983. Rubin D C,Wenzel A E. One hundred years of forgetting: A quantitative description of retention. Psychological Review, 1996, 103(4): 734-760. Tulving E. What is episodic memory? Current Directions in Psychological Science, 1993, 2(3): 67-70. Wiggs C L, Weisberg J, Martin A. Neural correlates of semantic and episodic memory retrieval. Neuropsychologia, 1999, 37(1): 103-118. Ding Y, Li X. Time weight collaborative filtering. In Proc. the 14th ACM International Conference on Information and Knowledge Management, Oct. 2005, pp.485-492. Fagin R, Lotem A, Naor M. Optimal aggregation algorithms for middleware. In Proc. the 20th ACM SIGMODSIGACT-SIGART Symposium on Principles of Database Systems, May 2001, pp.102-113. Lafferty J D, McCallum A, Pereira F C N. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proc. the 18th International Conference on Machine Learning, June 28–July 1, 2001, pp.282-289.