In camera calibration,accurate estimation of homography matrix between the world coordinates of the calibration board and its image coordinates is a key step in high-precision calibration of intrinsic camera parameter...In camera calibration,accurate estimation of homography matrix between the world coordinates of the calibration board and its image coordinates is a key step in high-precision calibration of intrinsic camera parameters.The existing homography matrix estimation methods have problems such as dependence on thresholds,low computational efficiency,and initial model or sorting quality affecting results.In this paper,a homography matrix estimation method based on adaptive genetic algorithm was proposed.Firstly,a new circular grid calibration board was designed and the strategy of first sampling of data sets was optimized.Secondly,a mathematical model for the estimated homography matrix was established according to the adaptive genetic algorithm.Thereby the optimal homography matrix between the calibration board and its image was obtained.Finally,the intrinsic camera parameters were calculated based on Zhang’s calibration method.The experimental results show that compared with the results of three traditional estimation methods RANSAC,PROSAC,and LMEDS,the reprojection error of the images by our estimation method is reduced by about 4.11%-7.85%,11.94%-16.91%,and 10.19%-17.82%,respectively;and the average running time of the algorithm decreases by about 25.85%-37.47%,11.99%-22.71%,and 46.50%-53.35%,respectively.In addition,the homography matrix estimation method in this paper was applied to camera calibration.The results show that compared with the traditional estimation method,the average accuracy of the camera during the calibration process increases by about 5.48%,15.06%,and 11.47%,respectively;and the average calibration efficiency of the camera is improved by about 10.13%,5.71%,and 14.26%,respectively.The homography matrix estimation method proposed in this paper not only obtained reliable results,but also had certain value and significance in improving the estimation accuracy and calculation efficiency in camera calibration.展开更多
The distribution of winter-spring snow cover over the Tibetan Plateau （TP） and its relationship with summer precipitation in the middle and lower reaches of Yangtze River Valley （MLYRV） during 2003-2013 have been ...The distribution of winter-spring snow cover over the Tibetan Plateau （TP） and its relationship with summer precipitation in the middle and lower reaches of Yangtze River Valley （MLYRV） during 2003-2013 have been investigated with the moderate-resolution imaging spectrometer （MODIS） Terra data （MOD10A2） and precipitation observations. Results show that snow cover percentage （SCP） remains approximately 20% in winter and spring then tails off to below 5% with warmer temperature and snow melt in summer. The lower and highest percentages present a declining tendency while the middle SCP exhibits an opposite variation. The maximum value appears from the middle of October to March and the minimum emerges from July to August. The annual and winter-spring SCPs present a decreasing tendency. Snow cover is mainly situated in the periphery of the plateau and mountainous regions, and less snow in the interior of the plateau, basin and valley areas in view of snow cover frequency （SCF） over the TP. Whatever annual or winter-spring snow cover, they all have remarkable declining tendency during 2003-2013, and annual snow cover presents a decreasing trend in the interior of the TP and increasing trend in the periphery of the TP. Hie multi-year averaged eight-day SCP is negatively related to mean precipitation in the MLYRV. Spring SCP is negatively related to summer precipitation while winter SCP is positively related to summer precipitation in most parts of the MLYRV. Hence, the influence of winter snow cover on precipitation is much more significant than that in spring on the basis of correlation analysis. The oscillation of SCF from southeast to northwest over the TP corresponds well to the beginning,development and cessation of the rain belt in eastern China.展开更多
基金supported by Anhui Province Key Research and Development Program(No.2022107020012).
文摘In camera calibration,accurate estimation of homography matrix between the world coordinates of the calibration board and its image coordinates is a key step in high-precision calibration of intrinsic camera parameters.The existing homography matrix estimation methods have problems such as dependence on thresholds,low computational efficiency,and initial model or sorting quality affecting results.In this paper,a homography matrix estimation method based on adaptive genetic algorithm was proposed.Firstly,a new circular grid calibration board was designed and the strategy of first sampling of data sets was optimized.Secondly,a mathematical model for the estimated homography matrix was established according to the adaptive genetic algorithm.Thereby the optimal homography matrix between the calibration board and its image was obtained.Finally,the intrinsic camera parameters were calculated based on Zhang’s calibration method.The experimental results show that compared with the results of three traditional estimation methods RANSAC,PROSAC,and LMEDS,the reprojection error of the images by our estimation method is reduced by about 4.11%-7.85%,11.94%-16.91%,and 10.19%-17.82%,respectively;and the average running time of the algorithm decreases by about 25.85%-37.47%,11.99%-22.71%,and 46.50%-53.35%,respectively.In addition,the homography matrix estimation method in this paper was applied to camera calibration.The results show that compared with the traditional estimation method,the average accuracy of the camera during the calibration process increases by about 5.48%,15.06%,and 11.47%,respectively;and the average calibration efficiency of the camera is improved by about 10.13%,5.71%,and 14.26%,respectively.The homography matrix estimation method proposed in this paper not only obtained reliable results,but also had certain value and significance in improving the estimation accuracy and calculation efficiency in camera calibration.
基金supported by the National Natural Science Foundation of China(Grant No.41130960)the Project of the China Meteorological Administration(Grant Nos.CCSF201515 and CMAGJ2013M51)
文摘The distribution of winter-spring snow cover over the Tibetan Plateau （TP） and its relationship with summer precipitation in the middle and lower reaches of Yangtze River Valley （MLYRV） during 2003-2013 have been investigated with the moderate-resolution imaging spectrometer （MODIS） Terra data （MOD10A2） and precipitation observations. Results show that snow cover percentage （SCP） remains approximately 20% in winter and spring then tails off to below 5% with warmer temperature and snow melt in summer. The lower and highest percentages present a declining tendency while the middle SCP exhibits an opposite variation. The maximum value appears from the middle of October to March and the minimum emerges from July to August. The annual and winter-spring SCPs present a decreasing tendency. Snow cover is mainly situated in the periphery of the plateau and mountainous regions, and less snow in the interior of the plateau, basin and valley areas in view of snow cover frequency （SCF） over the TP. Whatever annual or winter-spring snow cover, they all have remarkable declining tendency during 2003-2013, and annual snow cover presents a decreasing trend in the interior of the TP and increasing trend in the periphery of the TP. Hie multi-year averaged eight-day SCP is negatively related to mean precipitation in the MLYRV. Spring SCP is negatively related to summer precipitation while winter SCP is positively related to summer precipitation in most parts of the MLYRV. Hence, the influence of winter snow cover on precipitation is much more significant than that in spring on the basis of correlation analysis. The oscillation of SCF from southeast to northwest over the TP corresponds well to the beginning,development and cessation of the rain belt in eastern China.
