H.264 is an advanced video coding standard with wide application prospects. It has excellent compression performance and excellent image coding quality. It is widely used in many common fields such as video transmission, video storage and video editing. H. 264 uses a lot of complex computation, in which motion estimation takes up the largest amount of computation. Efficient motion estimation algorithm is of great significance to improve the efficiency of video coding. In this paper, the motion estimation and its typical algorithms of H.264 video coding standard are studied, focusing on UMHexagons (hereinafter referred to as UMH), the initial prediction order of motion vector and 5×5 spiral full search template is optimized, greatly improving the search efficiency.
In the three-dimensional reconstruction based on camera pair, the angle between two cameras should have a great influence on the reconstruction accuracy. When we shoot around the scene, when the angle between the camera axis is small, it is easy to match the images, but it is not conducive to restoring the three-dimensional coordinates. But when the angle between the two cameras axis is large, it is conducive to restoring the three-dimensional points, but it is not conducive to matching between the images, so there is an optimal position relationship. In this paper, the best position relationship between cameras is found through experiments and analysis. In addition, the matching algorithm is improved to resolve the contradiction mentioned above to a certain extent. The measures adopted are window adaptive matching and rotation matching. Experiments show that both methods are effective.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.