Personalized portraits ranking
Lei Huang, Tian Xia, Ji Wan, Yongdong Zhang, Shouxun Lin · 2011
Portraits, also known as images of people, constitute an important part of consumer photos. Existing methods manage portraits based on either explicit objectives, e.g., a specified person or event, or aesthetics, i.e., the aesthetic quality of portraits. This paper presents a novel system for personalized portraits ranking. First, four kinds of personalized features, i.e., composition, clothing style, affection and social relationship are proposed to quantify users' intent. Then, example-based and sketch-based user interfaces (UI) are developed, which are capable of capturing users' personal intent hardly described by queries or aesthetics. Finally, portraits ranking is implemented by combing these features together with the developed user interfaces. Experimental results show that the system performs well in providing personalized preferences and the proposed features are effective for portraits ranking. From the user study, our system gets promising results.