Abstract. In this paper, we proposed a method of calibrating the camera of smart phone based on web image. In order to achieve the goal, a website and the corresponding app are built: the website is used for displaying the calibrating pattern; the app is used to grab the image in real time and guide the user to rotate the smart phone so as to acquiring more precise parameters. Although the rough extrinsic parameters can be computed for the guiding procedure, the high computational complexity inhibits it from applying in the app. Instead, due to the regularity of the calibrating pattern-a chessboard, the vanishing points can be obtained by estimating the Intersection of parallel lines. The rotating angle can be roughly estimated by vanishing points. The proposed method can be applied in a number of different applications which need to calibrate the camera.
In phase-shifting profilometry based on the Gray code, the jump error
is inevitably generated and is further amplified in dynamic scenes. To
tackle this problem, we propose the robust tripartite complementary
Gray code method (TCG). Without projecting additional patterns, TCG
uses different combinations of Gray code to calculate three
complementary orders able to avoid jump error in the unwrapping
process. TCG is efficient and robust, as it fully utilizes the
redundant information of the Gray code. Experimental results
demonstrate that TCG can realize high-efficiency and high-speed
three-dimensional shape measurement at a rate of 500 fps.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.