Optimizing Aesthetic-based Photo Retargeting

• Main Authors: Chi-Cheng Huang, 黃啟承
• Other Authors: Damon Shing-Min Liu
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/fkz7d3

碩士 === 國立中正大學 === 資訊工程研究所 === 103 === Capabilities of camera are becoming more diverse. Photography is an art based on light, and its results are impacted on using the light directly. Modern cameras have automatic white balance, auto exposure and auto focus functions, so that we can easily take good photos with right exposure and focus setting. However, a nice photo depends not only on light used, its composition is also an important factor. Because the camera cannot know how to use the composition concept of photos, we therefore exploit the state-of-the-art retargeting technique to adjust photos for conforming the aesthetic composition. Color processing on photos does not destroy the original structure or details, and the related works are becoming mature; consequently we only have to focus on photo composition issues. For common retargeting methods, the subjects of photo must be preserved completely. The compound operator method for photo retargeting has become more popular, but they do not examine the photo content, and therefore explore the suitable techniques. They use one kind or a combination of multiple techniques to get the ideal photos, which limits the types of photos that can be processed. Instead, our approach can use suitable retargeting techniques, and coordinate the composition of original photos to make the photos conform the aesthetic rules. For the requirements of users, the photo types in our system apply not only to single photo but also to group photo, this part has not been explored in existing literature. We analyze the common rules of composition, and propose the rules applied to suit group photos. Besides, the photos are adjusted based on the human face. Because the faces always catch our eyes more than other parts. Finally, we conduct an objective user study to verify our system. We believe that using the development of our research, everyone can take an ideal photo.