tailieunhanh - Aesthetic Guideline Driven Photography by Robots

When a person in any culture has contempt, the opposites of difference and sameness are seen in a terrible, false way: one looks down on others and does not see how they are LIKE oneself. And this makes oneself feel bad. Native Americans of the Northwest Coast are described as swinging from arrogance to self-abasement: "from triumph to shame" (Ruth Benedict, Patterns of Culture, p. 220). This is how I felt. It is a notable fact that people of the Northwest coast came to an art form that criticizes what they were doing as a society, and as people. They created a design which, Franz Boas. | Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence Aesthetic Guideline Driven Photography by Robots Raghudeep Gadde and Kamalakar Karlapalem Center for Data Engineering International Institute of Information Technology - Hyderabad India kamal@ Abstract Robots depend on captured images for perceiving the environment. A robot can replace a human in capturing quality photographs for publishing. In this paper we employ an iterative photo capture by robots by repositioning itself to capture good quality photographs. Our image quality assessment approach is based on few high level features of the image combined with some of the aesthetic guidelines of professional photography. Our system can also be used in web image search applications to rank images. We test our quality assessment approach on a large and diversified dataset and our system is able to achieve a classification accuracy of 79 . We assess the aesthetic error in the captured image and estimate the change required in orientation of the robot to retake an aesthetically better photograph. Our experiments are conducted on NAO robot with no stereo vision. The results demonstrate that our system can be used to capture professional photographs which are in accord with the human professional photography. 1 Introduction The goal of this work is to get robots to take good photographs that are coherent with humans perception. In this research we categorize the initially captured photographs into two classes namely good and bad quality images by assessing their visual appeal. We then recapture if required a better photograph according to the aesthetic composition guidelines of professional photography by changing the orientation of the robot camera or the part containing camera. A computationally efficient image quality assessment technique and a methodology to estimate the desired change in the orientation is required to recapture an