摘要
相比单特征,多图像特征的组合提供更多的场景判别信息,可以提高检测精度,但需要设计合适的组合准则.文中提出多特征组合的加权方法,把特征组合的闭环检测精度表示为正确匹配和错误匹配的图像对在特征空间中距离分布的Rényi散度,最优特征组合为最大化Rényi散度.分析验证Rényi散度的参数与对应最优特征组合的闭环检测性能之间的关系.实验表明,文中方法可以提高闭环检测精度.当Rényi散度的参数取0.75~1时,最优特征组合性能最佳.
Multiple image features provide more discriminative information of the scenes compared with individual feature, and thus the performance of loop closure detection （LCD） is improved. However, a suitable combination criterion is vital. A weighting method of multiple feature combination is proposed. The accuracy of LCD of the feature combination is expressed as the Renyi divergence of the distance distributions of true matches and false matches in the feature space. The optimal feature combination maximizes the Renyi divergence. The relationship between the parameter of Renyi divergence and the performance of LCD of the optimal feature combination is analyzed and experimentally verified. The experiments show that the proposed method improves the performance of LCD significantly and the best performance is achieved with the parameter of Renyi divergence being from 0.75 to 1.
作者
王小龙
彭国华
WANG Xiaolong;PENG Guohua(Department of Applied Mathematics, School of Natural and Applied Sciences, Northwestern Polytechnical University, Xi＇ an 710129)
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2018年第5期389-397,共9页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.61201323)、陕西省自然科学基金(No.2017JM6026)资助
