Tags Re-ranking Using Multi-level Features in Automatic Image Annotation
Subject Areas : Image, Speech and Signal ProcessingForogh Ahmadi 1 , Vafa Maihami 2
1 - Department of Computer Engineering, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran
2 - Department of Computer Engineering, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran
Keywords:
Abstract :
[1] R. Datta, D. Joshi, J. Li, and J. Z. Wang, “Image retrieval: Ideas, influences, and trends of the new age,” ACM Comput. Surv., vol. 40, no. 2, pp. 1–60, Apr. 2008.
[2] X. Chang, H. Shen, S. Wang, J. Liu, and X. Li, “Semi-supervised Feature Analysis for Multimedia Annotation by Mining Label Correlation,” pp. 74–85, 2014.
[3] X. Li, T. Uricchio, L. Ballan, M. Bertini, C. G. M. Snoek, and A. Del Bimbo, “Socializing the semantic gap: A comparative survey on image tag assignment, refinement, and retrieval,” ACM Comput. Surv., vol. 49, no. 1, pp. 1–39, Jun. 2016.
[4] M. Wang, B. Ni, X.-S. Hua, and T.-S. Chua, “A survey of multimedia tagging with human-computer joint exploration.,” ACM Comput. Surv., vol. 44, no. 4, pp. 1–24, Aug. 2012.
[5] Yue Gao, Meng Wang, Zheng-Jun Zha, Jialie Shen, Xuelong Li, and Xindong Wu, “Visual-Textual Joint Relevance Learning for Tag-Based Social Image Search,” IEEE Trans. Image Process., vol. 22, no. 1, pp. 363–376, Jan. 2013.
[6] Y. Liu, D. Zhang, G. Lu, and W.-Y. Ma, “A survey of content-based image retrieval with high-level semantics,” Pattern Recognit., vol. 40, no. 1, pp. 262–282, Jan. 2007.
[7] D. Zhang, M. M. Islam, and G. Lu, “A review on automatic image annotation techniques,” Pattern Recognit., vol. 45, no. 1, pp. 346–362, Jan. 2012.
[8] A. E. Brito, D. Kletter, M. Singhal, and M. Bern, “Benchmark study of automatic annotation of MALDI-TOF N-glycan profiles,” J. Proteomics, vol. 129, pp. 71–77, Nov. 2015.
[9] S. Protasov, A. M. Khan, K. Sozykin, and M. Ahmad, “Using deep features for video scene detection and annotation,” Signal, Image Video Process., pp. 1–9, Jan. 2018.
[10] X. Xirong Li, C. G. M. Snoek, and M. Worring, “Learning Social Tag Relevance by Neighbor Voting,” IEEE Trans. Multimed., vol. 11, no. 7, pp. 1310–1322, Nov. 2009.
[11] D. Tian and Z. Shi, “Automatic image annotation based on Gaussian mixture model considering cross-modal correlations,” J. Vis. Commun. Image Represent., vol. 44, pp. 50–60, Apr. 2017.
[12] K. Akhilesh and R. R. Sedamkar, “Automatic image annotation using an ant colony optimization algorithm (ACO),” in 2016 IEEE 7th Power India International Conference (PIICON), 2016, pp. 1–4.
[13] Q. Cheng, Q. Zhang, P. Fu, C. Tu, and S. Li, “A survey and analysis on automatic image annotation,” Pattern Recognit., vol. 79, pp. 242–259, Jul. 2018.
[14] S. Lee, W. De Neve, and Y. M. Ro, “Visually weighted neighbor voting for image tag relevance learning,” Multimed. Tools Appl., vol. 72, no. 2, pp. 1363–1386, Apr. 2013.
[15] G. Carneiro, A. B. Chan, P. J. Moreno, and N. Vasconcelos, “Supervised Learning of Semantic Classes for Image Annotation and Retrieval,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 3, pp. 394–410, Mar. 2007.
[16] T. Uricchio, L. Ballan, M. Bertini, and A. Del Bimbo, “An evaluation of nearest-neighbor methods for tag refinement,” in 2013 IEEE International Conference on Multimedia and Expo (ICME), 2013, pp. 1–6.
[17] T. Uricchio, L. Ballan, L. Seidenari, and A. Del Bimbo, “Automatic image annotation via label transfer in the semantic space,” Pattern Recognit., vol. 71, pp. 144–157, Nov. 2017.
[18] X. Zhu, W. Nejdl, and M. Georgescu, “An adaptive teleportation random walk model for learning social tag relevance,” in Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR ’14, 2014, pp. 223–232.
[19] Z. Li, J. Liu, C. Xu, and H. Lu, “MLRank: Multi-correlation Learning to Rank for image annotation,” Pattern Recognit., vol. 46, no. 10, pp. 2700–2710, Oct. 2013.
[20] J. Johnson, L. Ballan, and L. Fei-Fei, “Love Thy Neighbors: Image Annotation by Exploiting Image Metadata,” in 2015 IEEE International Conference on Computer Vision (ICCV), 2015, pp. 4624–4632.
[21] C. Cui, J. Shen, J. Ma, and T. Lian, “Social tag relevance learning via ranking-oriented neighbor voting,” Multimed. Tools Appl., vol. 76, no. 6, pp. 8831–8857, Mar. 2017.
[22] D. Liu, X.-S. Hua, L. Yang, M. Wang, and H.-J. Zhang, “Tag ranking,” in Proceedings of the 18th international conference on World wide web - WWW ’09, 2009, p. 351.
[23] Y. Wang, X. Lin, L. Wu, and W. Zhang, “Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval,” IEEE Trans. Image Process., vol. 26, no. 3, pp. 1393–1404, Mar. 2017.
[24] L. Ballan, M. Bertini, G. Serra, and A. Del Bimbo, “A data-driven approach for tag refinement and localization in web videos,” Comput. Vis. Image Underst., vol. 140, pp. 58–67, Nov. 2015.
[25] T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y. Zheng, “NUS-WIDE: a real-world web image database from National University of Singapore,” in Proceeding of the ACM International Conference on Image and Video Retrieval - CIVR ’09, 2009.
[26] F. Tian, X. Shen, and X. Liu, “Multimedia automatic annotation by mining label set correlation,” Multimed. Tools Appl., vol. 77, no. 3, pp. 3473–3491, Feb. 2018.
[27] Maihami V, Yaghmaee F. Automatic image annotation using community detection in neighbor images. Physica A: Statistical Mechanics and its Applications. 1;507:123-32, 2018.
[28] Maihami V, Yaghmaee F. A genetic-based prototyping for automatic image annotation. Computers & Electrical Engineering. 1;70:400-12, 2018.
[29] Lotfi A, Maihami V, Yaghmaee F. Wood image annotation using gabor texture feature. Int. J. Mechatronics, Electr. Comput. Technol..;4:1508-23, 2014.
[30] Maihami V, Yaghmaee F. A review on the application of structured sparse representation at image annotation. Artificial Intelligence Review. 1;48(3):331-48, 2017.