A unified framework of predicting binary interestingness of images based on discriminant correlation analysis and multiple kernel learning

no code implementations • 14 Oct 2019 • Qiang Sun, Liting Wang, Maohui Li, Longtao Zhang, Yuxiang Yang

In the modern content-based image retrieval systems, there is an increasingly interest in constructing a computationally effective model to predict the interestingness of images since the measure of image interestingness could improve the human-centered search satisfaction and the user experience in different applications.

Content-Based Image Retrieval Retrieval