论文信息 - Face Recognition by Using SURF Features with Block-Based Bag of Feature Models

Face Recognition by Using SURF Features with Block-Based Bag of Feature Models

Face recognition is used to identify humans by their face image. Recently it becomes most common application in information security. Bag of features has been successfully applied in face recognition. In our research we use SURF features and try to improve it by using block-based bag of feature models. In this method we partition the image into multiple blocks and we extract SURF features densely on each block. We compare the performance of the original bag of feature model with Grid/Detector method and bag of block-based feature model.

Ahmed Salem | Tomoko Ozeki

[1] Gabriela Csurka,et al. Visual categorization with bags of keypoints , 2002, eccv 2004.

[2] Masahide Kaneko,et al. Face and expression recognition based on bag of words method considering holistic and local image features , 2010, 2010 10th International Symposium on Communications and Information Technologies.

[3] Luc Van Gool,et al. SURF: Speeded Up Robust Features , 2006, ECCV.

[4] Chunhui Zhao,et al. Bisecting k-means clustering based face recognition using block-based bag of words model , 2015 .

[5] Luc Van Gool,et al. Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..