摘要
针对基于稀疏表示的分类器算法复杂度高、识别速度较慢的问题,提出了基于级联稀疏表示分类器的人脸识别算法。该算法采用级联的思想,通过多次重复使用基于稀疏表示的分类器,逐级精确确定待分类样本所在的类,降低了计算复杂度和识别难度,达到了识别率高、鲁棒性强、识别速度快的目标。
For representation-based representation-based problem classifier classifier of high complexity, slow identification of algorithm based on sparse , the paper proposed face. The algorithm uses ideas recognition algorithm based on cascade sparse of cascade, through repeated using of sparse representation-based classifier to determine the class which the sample to be classified belongs to step by step and accurately. The algorithm reduces computational complexity and identifying difficulty, and reaches goals of high recognition rate, good robustness and fast identifying speed.
出处
《工矿自动化》
北大核心
2014年第5期46-48,共3页
Journal Of Mine Automation
基金
国家自然科学基金项目(61240050)
关键词
人脸识别
级联稀疏表示分类器
识别率
鲁棒性
face recognition
cascade sparse representation-based classifier
recognition rate
robustness