摘要
该文在随机抽样一致性算法基础上,提出了一个基于预检验的随机抽样一致性PreviewmodelParametersEvaluationRANSAC(PERANSAC)消失点估计算法:该算法在原始RANSAC算法消失点检验前,加入一个预检验步骤,在保证计算结果精度不变的前提下,过滤掉大量偏差较大的消失点,减少了检验的计算量,大大提高了算法的整体效率。大量的实验结果表明,该算法的计算精度与RANSAC算法精度保持一致,计算速度远高于RANSAC算法。
Preview model Parameters Evaluation RANSAC algorithm （PERANSAC） is given in vanishing point detecting A preview model parameters evaluation selection is added in the RANSAC algorithm. With guaranteeing the same confidence of the solution as RANSAC, a very large number of erroneous vanishing point obtained from contaminated samples are discarded in the preview evaluation selection. The time of evaluating the quality of the vanishing point is reduced. RANSAC efficiency is significantly improved. PERANSAC algorithm is evaluated on real-world images, a significant increase in speed is shown and the solutions are same as RANSAC.
出处
《电子与信息学报》
EI
CSCD
北大核心
2006年第8期1458-1462,共5页
Journal of Electronics & Information Technology
