在本論文中，我們提出一個自動的方法有效的對照片進行管理，目標是從一起出遊的朋友們所拍攝的多組旅遊照片中建構出代表性的照片集，而這類型照片的特性是彼此間會有很高的相似度。首先，我們提出一個基於生物資訊學上比對基因序列之間相似度的演算法，並將其應用在相似照片序列的比對上。接著利用比對的結果將兩組不同的照片序列進行有效的合併。接著，我們進一步的提出一個照片評分方法，對合併後的照片序列進行評分的工作，最後保留分數較高的照片來當做代表性的照片集。有別於以往對照片評分的方法，皆是對單一照片直接進行評分的工作，我們則是利用了相似場景中其它相似的照片來輔助對單一照片的評分。在實驗上，我們收集了22個使用者所拍攝的照片來驗證我們所提出的方法。

In this paper, we develop automatic approaches for effectively managing photos. In particular, we aim to find a representative stream of travel photos taken with friends in the same trip. One characteristic of such photos is that they tend to share similar contents despite the fact that they are taken by different people. Based on the observation, we first propose a method to combine multiple photo sequences into a photo stream. It is inspired by sequence alignment techniques in bioinformatics for finding similar DNA and protein sequences. Next, we develop an aesthetic quality assessment method to score each photo. Photos with higher scores are retained and formed the representative photo stream. Unlike conventional approaches that solely use information within the photo under evaluation, we show that information of the near duplicate images—which are mostly available in travel photos—could be used to facilitate the quality assessment problem. Experimental results using travel photos collected from 22 users validate the effectiveness of proposed approaches.

[1] S. Bhattacharya, R. Sukthankar, and M. Shah. A framework for photo-quality assessment and enhancement based on visual aesthetics. In Proceedings of the ACM international conference on Multimedia, pages 271–280, 2010.
[2] W.T. Chu and C.H. Lin. Automatic selection of representative photo and smart thumbnailing using near-duplicate detection. In Proceeding of the 16th ACM international conference on Multimedia, pages 829–832, 2008.
[3] W.T. Chu, C.H. Lin, and J.Y. Yu. Feature classification for representative photo selection. In Proceedings of the 17th ACM international conference on Multimedia, pages 509–512, 2009.
[4] F. Crete, T. Dolmiere, P. Ladret, and M. Nicolas. The blur effect: perception and estimation with a new no-reference perceptual blur metric. Human Vision and Electronic Imaging XII, 6492:11.
[5] R. Datta, D. Joshi, J. Li, and J. Wang. Studying aesthetics in photographic images using a computational approach. Proceedings of the European Confer- ence on Computer Vision, pages 7–13, 2006.
[6] H. Drucker, C.J.C. Burges, L. Kaufman, A. Smola, and V. Vapnik. Sup- port vector regression machines. Advances in neural information processing systems, pages 155–161, 1997.
[7] D. Hoiem, A.A. Efros, and M. Hebert. Recovering surface layout from an image. International Journal of Computer Vision, 75(1):151–172, 2007.
[8] Y. Ke, X. Tang, and F. Jing. The design of high-level features for photo quality assessment. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 419–426, 2006.
[9] Yan Ke and Rahul Sukthankar. Pca-sift: A more distinctive representation for local image descriptors. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 506–513, 2004.
[10] C. Li, A.C. Loui, and T. Chen. Towards aesthetics: a photo quality assess- ment and photo selection system. In Proceedings of the ACM international conference on Multimedia, pages 827–830, 2010.
[11] D.G. Lowe. Distinctive image features from scale-invariant keypoints. Inter- national journal of computer vision, 60(2):91–110, 2004.
[12] Y. Luo and X. Tang. Photo and video quality evaluation: Focusing on the subject. In Proceedings of the 10th European Conference on Computer Vision: Part III, pages 386–399, 2008.
[13] B. Mehta, S. Nangia, M. Gupta, and W. Nejdl. Detecting image spam us- ing visual features and near duplicate detection. In Proceeding of the 17th international conference on World Wide Web, pages 497–506, 2008.
[14] K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE transactions on pattern analysis and machine intelligence, pages 1615– 1630, 2005.
[15] S.B. Needleman and C.D. Wunsch. A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of molecular biology, 48(3):443–453, 1970.
[16] J.C. Platt, M. Czerwinski, and B.A. Field. Phototoc: Automatic clustering for browsing personal photographs. In Proceedings of the Joint Conference of the Fourth International Conference on Multimedia, pages 6–10, 2004.
[17] Y.M. Ro, M. Kim, H.K. Kang, BS Manjunath, and J. Kim. Mpeg-7 homoge- neous texture descriptor. ETRI journal, 23(2):41–51, 2001.
[18] H.R. Sheikh, A.C. Bovik, and G. de Veciana. An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Transactions on Image Processing, 14(12):2117–2128, 2005.
[19] H. Tong, M. Li, H.J. Zhang, J. He, and C. Zhang. Classification of digi- tal photos taken by photographers or home users. Advances in Multimedia Information Processing-PCM, pages 198–205, 2005.
[20] Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli. Image quality as- sessment: From error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4):600–612, 2004.
[21] Z. Wang, H.R. Sheikh, and A.C. Bovik. No-reference perceptual quality as- sessment of jpeg compressed images. Proceedings of IEEE International Con- ferencing on Image Processing, pages 477–480, 2002.
[22] C.H. Yeh, Y.C. Ho, B.A. Barsky, and M. Ouhyoung. Personalized photo- graph ranking and selection system. In Proceedings of the ACM international conference on Multimedia, pages 211–220, 2010.