目的提出一种结合C/S(Client/Server)架构和BRF(Boosted random ferns)算法的移动增强现实应用方案,以保证图像识别算法对于产品外包装的识别性能。方法 BRF是一种高效、鲁棒的特征匹配算法,但由于手机内存及处理器等硬件条件的制约,不...目的提出一种结合C/S(Client/Server)架构和BRF(Boosted random ferns)算法的移动增强现实应用方案,以保证图像识别算法对于产品外包装的识别性能。方法 BRF是一种高效、鲁棒的特征匹配算法,但由于手机内存及处理器等硬件条件的制约,不能直接适用于手机终端。将C/S模式与BRF算法相结合应用于图像特征匹配,并设计实验测试比较文中方案(CS-BRF)与ORB算法的识别速度和匹配精度。结果实验结果表明,相比ORB算法,CS-BRF在识别速度相近的前提下,具有更为优异的识别精度。结论 CS-BRF能够实时准确识别印刷品图像,良好适用于产品包装移动增强现实系统。展开更多
It is difficulties for the computer simulation method to study radiation regime at large-scale.Simplified coniferous model was investigated in the present study.It makes the computer simulation methods such as L-syste...It is difficulties for the computer simulation method to study radiation regime at large-scale.Simplified coniferous model was investigated in the present study.It makes the computer simulation methods such as L-systems and radiosity-graphics combined method(RGM) more powerful in remote sensing of heterogeneous coniferous forests over a large-scale region.L-systems is applied to render 3-D coniferous forest scenarios,and RGM model was used to calculate BRF(bidirectional reflectance factor) in visible and near-infrared regions.Results in this study show that in most cases both agreed well.Meanwhile at a tree and forest level,the results are also good.展开更多
文摘目的提出一种结合C/S(Client/Server)架构和BRF(Boosted random ferns)算法的移动增强现实应用方案,以保证图像识别算法对于产品外包装的识别性能。方法 BRF是一种高效、鲁棒的特征匹配算法,但由于手机内存及处理器等硬件条件的制约,不能直接适用于手机终端。将C/S模式与BRF算法相结合应用于图像特征匹配,并设计实验测试比较文中方案(CS-BRF)与ORB算法的识别速度和匹配精度。结果实验结果表明,相比ORB算法,CS-BRF在识别速度相近的前提下,具有更为优异的识别精度。结论 CS-BRF能够实时准确识别印刷品图像,良好适用于产品包装移动增强现实系统。
基金the Chinese National Natural Science Foundation Project(40701124)the Chinese Hi-tech Research and Development Program Project(2006AA12Z114)
文摘It is difficulties for the computer simulation method to study radiation regime at large-scale.Simplified coniferous model was investigated in the present study.It makes the computer simulation methods such as L-systems and radiosity-graphics combined method(RGM) more powerful in remote sensing of heterogeneous coniferous forests over a large-scale region.L-systems is applied to render 3-D coniferous forest scenarios,and RGM model was used to calculate BRF(bidirectional reflectance factor) in visible and near-infrared regions.Results in this study show that in most cases both agreed well.Meanwhile at a tree and forest level,the results are also good.
