Abstract
Various mobile devices with high-quality cameras are very popular in human daily life. Appropriate directions about the standing postures can greatly improve the user experience while taking photos. In this paper, we propose a method to recommend custom model-like standing style based on model sketches. We first translate the real images of splendid models into sketches by fast person detection and model sketching. The generated sketches are represented by the deep feature vectors. We design an iterative detection approach to finding the most representative model sketches. For a user-input image, the model-like standing styles are recommended in form of the sketch. Besides, we introduce a novel method to score the standing posture of the input image through multi-Gaussian functions. Finally, the experimental results on the Model Standing Style (MSS) dataset demonstrate the effectiveness of the proposed approach.
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Acknowledgements
The work was supported in part by the National Science Foundation of China (No. 61472103). We especially would like to thank the China Scholarship Council (CSC) for funding the first author to conduct the partially of this project at Australian National University.
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Zheng, Y., Yao, H., Wang, D. (2018). Sketch Based Model-Like Standing Style Recommendation. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10735. Springer, Cham. https://doi.org/10.1007/978-3-319-77380-3_79
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