Aesthetic Guidelines Driven Photography By Robots
Raghudeep Gadde and Kamalakar Karlapalem
Robots depend on images captured 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. This system can also be used in web image search applications. We test our quality assessment approach on a large and diversified dataset and our system is able to achieve a classification rate of 79%. We assess the aesthetic error in the captured image and rationally estimate the change required in orientation of the robot, using which it can retake an aesthetically better photograph. The experiments are conducted on NAO robot with no stereo vision. The results demonstrate that this system can be used to capture professional photographs that are in accord with the human professional photography. Further, we show that the computation cost for processing these quality images is less and the clarity of the segments detected from these photographs is high.