4:00 PM - 4:20 PM
[3D5-OS-22b-02] Photograph creation analysis based multiple evaluation features to acquire filming techniques
Keywords:Photograph creation, Filmcraft support, Machine Learning
Recently, numerous people take photographs easily by smart-phones and post them on social network services. On the other hand, huge knowledge and technique are required in order to become skilled photographers. It is hard to acquire these information especially on real-time filming.
Thus, the aim of the research is to create a system to suggest advices for novices of photographers.To construct such a system, the method to evaluate photos precisely like a professional photographer is required.
In this paper, we have proposed original dataset of scenery photographs with detailed scores by professional photographers and construct Deep Convolutional Neural Networks to classify two class images with the labels evaluated by the author as a professional photographer. In addition, we consider acquired features by Gradient Weighted Class Activation Mapping.
Thus, the aim of the research is to create a system to suggest advices for novices of photographers.To construct such a system, the method to evaluate photos precisely like a professional photographer is required.
In this paper, we have proposed original dataset of scenery photographs with detailed scores by professional photographers and construct Deep Convolutional Neural Networks to classify two class images with the labels evaluated by the author as a professional photographer. In addition, we consider acquired features by Gradient Weighted Class Activation Mapping.
Authentication for paper PDF access
A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.