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標題:On the Design of a Photo Beauty Measurement Mechanism Based on Image Composition and Machine Learning
學年
學期
出版(發表)日期2017/10/25
作品名稱On the Design of a Photo Beauty Measurement Mechanism Based on Image Composition and Machine Learning
作品名稱(其他語言)
著者C. S. Fahn; M. L. Wu
單位
出版者IntechOpen
著錄名稱、卷期、頁數Perception of Beauty
摘要In this chapter, we propose a machine learning scheme on how to measure the beauty of a photo. Different from traditional measurements that focus on the quality of captured signals, the beauty of photos is based on high-level concepts from the knowledge of photo aesthetics. Because the concept of beauty is mostly defined by human being, the measurement must contain some knowledge obtained from them. Therefore, our measurement can be realized by a machine learning mechanism, which is trained by collected data from the human. There are several computational aesthetic manners used for building a photo beauty measurement system, including low-level feature extraction, image composition analysis, photo semantics parsing, and classification rule generation. Because the meaning of beauty may vary from different people, the personal preference is also taken into consideration. In this chapter, the performance of two computational aesthetic manners for the perception of beauty is evaluated, which are based on image composition analysis and low-level features to determine whether a photo meets the criterion of a professional photographing via different classifiers. The experimental results manifest that both decision tree and multilayer perceptron-based classifiers attain high accuracy of more than 90% for evaluation.
關鍵字computational aesthetics;photo beauty measurement;image composition;machine learning;decision tree;multilayer perceptron
語言英文(美國)
ISBN
相關連結
SDGs
  • 優質教育,尊嚴就業與經濟發展,產業創新與基礎設施
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