个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:数学科学学院
学科:计算数学
办公地点:创新园大厦(海山楼)B1313
联系方式:84708351-8093
电子邮箱:zxsu@dlut.edu.cn
Adaptive Weighted Deformable Part Model for Object Detection
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论文类型:会议论文
发表时间:2018-01-01
收录刊物:CPCI-S、EI
页面范围:72-75
关键字:Object detection; DPM; Pedestrian detection
摘要:We describe an adaptive weighted deformable part model for object detection based on traditional deformable part model(DPM). In the original DPM model, we find that the high response score region calculated by the template filter as high-energy regions, which indicates that the influence on the detection results is greater. The parts can affect the results of object detection, some important parts may directly determine the accuracy of the results, and some unimportant parts even produce bad impacts. To reduce the adverse effects caused by unimportant part filter, we add an adaptive coefficient strategy to the traditional method, which could improve the accuracy of object detection without efficiency loss. The proposed algorithm is better in accuracy compared with the traditional deformable part model, especially in the case of occlusion, with the same efficiency.