摘要
提出一种基于网格的统计模型的三维目标识别算法。首先将网格结构引入多视点图像,并针对网格位置,利用三维目标多视点间的关联性,再根据目标的局部不变特征建立统计模型;其次对图像数据库COIL中三维目标的自由度进行扩充;最后在此基础上,对算法的识别性能进行测试。实验结果表明,该算法不仅能有效识别三维目标的类别,而且能够对目标的姿态做出可靠的判断,具有较强的鲁棒性。
A 3D object recognition algorithm based on statistical model of grid structure is presented in this paper. First, a grid structure is introduced into the muhi-view points image. Then according to the positions of the grids, the relationship between the multi-view points of the 3D object and the local invariant features of the object, the statistical model is established. Second, the degrees of freedom of the 3D object, which is from the image database-COIL, are expanded. At last, based on the previous work, the recognition performance of this algorithm is tested. The empirical results illustrate that this 3D object recognition algorithm, with relatively strong robustness, can not only recognize the classification of 3D objects effectively, but also make reliable judg- ments on the attitudes of the objects.
出处
《计算机与现代化》
2014年第4期24-28,共5页
Computer and Modernization
基金
国家自然科学基金资助项目(61101191)
航空基金资助项目(20130153003)
上海航天科技创新基金资助项目(SAST201342)
关键词
三维目标识别
多视点
网格结构
目标姿态识别
3D object recognition
multiple views
grid structure
object pose recognition
