吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (6): 1909-1917.doi: 10.13229/j.cnki.jdxbgxb201706032
• Orginal Article • Previous Articles Next Articles
FAN Min1, HAN Qi1, WANG Fen1, SU Xiao-lan2, XU Hao2, WU Song-lin2
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[1] Forsyth D A, Ponce J. Computer Vision: a modern approach[M]. New Jersey: Pearson Educacion Inc., 2002. [2] Xiao J X, Hays J, Ehinger K A, et al. Sundatabase: large-scale scene recognition from abbeyto zoo[C]//IEEE Conference on Computer Vision and Pattern Reco-gnition (CVPR), San Francisco, California, USA, 2010:3485-3492. [3] 李学龙,史建华,董永生,等. 场景图像分类技术综述[J].中国科学:信息科学,2015,45(7):827-848. Li Xue-long, Shi Jian-hua, Dong Yong-sheng, et al. Summarize of scene image classification technology[J].Science China Information Sciences, 2015, 45(7):827-848. [4] Lowe D G. Distinctive image features from scaleinvariantkeypoints[J]. International Journal of Computer Vision, 2004, 60(2):91-110. [5] Oliva A, Torralba A. Modeling the shape of the scene: a holistic representation of the spatial envelope[J].International Journal of Computer Vision, 2001, 42(3): 145-175. [6] Dalal N, Triggs B. Histograms of oriented gradientsfor human detection[C]//IEEE Conference on Computer Vision and Pattern Recognition(CVPR), San Diego, CA, USA, 2005, 1(12):886-893. [7] 刘萍萍,赵宏伟,耿庆田,等.基于局部特征和视皮层识别机制的图像分类[J]. 吉林大学学报:工学版, 2011, 41 (5): 1401-1406. Liu Ping-ping,Zhao Hong-wei,Geng Qing-tian, et al.Image classification method based on local feature and visual cortex recognition mechanism[J]. Journal of Jilin University (Engineering and Technology Edition), 2011, 41(5):1401-1406. [8] Yang J, Yu K, Gong Y, et al. Linear spatial pyramidmatching using sparse coding for image classification[C]//Computer Society Conference on Computer Vision and Pattern Recognition(CVPR), Miami, FL, 2009: 1794-1801. [9] Wang J, Yang J, Yu K, et al. Locality-constrained lin-ear coding for image classification[C]//Computer Society Conference on Computer Vision and Pattern Rec-ognition (CVPR),San Francisco, California, USA, 2010, 119(5):3360-3367. [10] Xi Peng, Rui Yan, Bo Zhao, et al. Fast low rank representation based spatial pyramid matching for image classification[J]. Knowledge Based Systems, 2015, 90(C):14-22. [11] Datta R, Joshi D, Li J. Image retrieval: ideas, influences, and trends of the new age[J].ACM, Computing Surveys, 2008, 40(2): 1-60. [12] 陈涛, 邓辉舫, 刘靖. 基于密度聚类和多示例学习的图像分类方法[J]. 吉林大学学报:工学版, 2014, 44 (4):1126-1134. Chen Tao,Deng Hui-fang,Liu Jing. Image categorization method using density clustering on region features and mutiinstance learning[J]. Journal of Jilin University (Engineering and Technology Edition), 2014, 44 (4):1126-1134. [13] Li L J, Su H, Xing E P, et al. Object bank: a highlevel image representation for scene classification & s-emanticfeature sparsification[J]. Advances in Neural Information Proceedings Systems, Vancouver, 2010, 26 (6):719-729. [14] Li Li-jia, Su Hao, Lim Yong-whan , et al. Objects as attributes for scene classification[J]. Trends and Topics in Computer Vision, 2010, 6553: 57-69. [15] Juneja M, Vedialdi A, Jawahar C V, et al. Blocks thatshout: distinctive part for scene classification[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, OR USA, 2013, 9(4):923-930. [16] Sadeghi F, Tappen M F. Latent pyramidal regions for recognizing scenes[C]//European Conference on Computer Vision (ECCV), Firenze, Italy, 2012, 7576(1): 228-241. [17] Yu Jun, Tao Da-cheng, Rui Yong, et al. Pairwise constrains based multiview features fusion for scene classification[J]. Pattern Recognition, 2013, 46(2):483-396. [18] Luo Y, Tao D, Xu C, et al. Multiview vector-valued manifold regularization for multilabel image classification[J].IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(5):709-722. [19] Fan Min, Wang Fen, et al. Fast locality-constrained low-rank coding for image classification[C]//The Chinese Automation Congress (CAC), Wuhan, China, 2015:644-650. [20] Felzenszwalb P, McAllester D, Ramanan D. A discriminatively trained, multiscale, deformable part model[C]//IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska, USA, 2008:1-8. [21] Felzenszwalb P, Girshick R B, McAllester D, et al. Object detection with discriminatively trained part-bas-ed models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(9): 1627-1645. [22] Andrews S, Tsochantaridis I, Hofmann T. Support vector machines for multiple-instance learning[J]. Advances in Neural Information Processing Systems, Vancouver, 2002, 15(2): 561-568. [23] Grauman K, Darrell T. Pyramid match kernels: Disc-riminative classification with sets of image features[C]//IEEE International Conference on Computer Vision (ICCV), Beijing, China, 2006:1458-1465. [24] Lazebnik S, Schmid C, Ponce J. Beyond bags of features: spatial pyramid matching for recognizingnatur-al scene categories[C]//IEEE Conference on Computer Vision and Pattern Recognition(CVPR), New York, NY, USA, 2006: 2169-2178. [25] Candes E, Recht B. Exact matrix completion via convex optimization[J]. Foundations of Computational Mathematics, 2008, 9: 712-717. [26] Lin Z, Ganesh A, Wright J, et al. Fast convex optimization algorithms for exact recovery of a corrupted lowrank matrix[J].Journal of the Marine Biological Association of the UK, 2009, 56(3):707-722. [27] Zhang H, Yi Z, Peng X. fLRR: fast low-rank repre-sentation using Frobenius-norm[J]. Electronics Letters, 2014, 50 (13):936-938. [28] Yu K, Zhang T, Gong Y. Nonlinear learning using lo-calcoordinate coding[C]//Proc of NIPS, 2009:2223-2231. [29] Yang Lei, Re Yan-yunn,Zhang Wen-qiang,et al. 3D depth image analysis for indoor fall detection of elderly people[J].Digital Communications & Networks, 2016, 2(1):24-33. [30] Xu H, Hua K, Wang H. Adaptive FEC coding and cooperative relayed wireless image transmission[J]. Digital Communications & Networks, 2015, 1(3):213-221. [31] Li L J,Li Fei-fei. What, where and who? classifyi-ng events by scene and object recognition[C]//IEEE International Conference on Computer Vision (ICCV), Rio de Janeiro,Brazil, 2007:1-8. [32] Li Fei-fei, Perona P. A Bayesian hierarchical model for learning natural scene categories[C]//IEEE Confer-ence on Computer Vision and Pattern Recognition (CVPR), San Diego, CA,USA, 2005:524-531. |
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