In order to solve the problem of difficult target matching and low matching efficiency in binocular measurement, this paper proposes a real-time target feature matching algorithm based on Binocular Stereo Vision-absolute window error minimization (CAEW, Calculate the Absolute Error Window ) to improve the speed and accuracy of measurements. Firstly, the calibration of the camera is solved by using Zhang's calibration method, and the Bouguet algorithm is used for Binocular Stereo Vision of the final calibration data. Then, the AdaBoost iterative algorithm is used to train the target detector for target recognition. The CAEW algorithm is compared with the commonly used SURF (Speeded-Up Robust Feature) algorithm. The evaluation data of experimental results showed that the CAEW algorithm can achieve an evaluation of more than 90%. It is significantly improved compared with the SURF algorithm and meet the needs of binocular real-time target matching.
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.