Face Recognition using SIFT Features
نویسنده
چکیده
Face recognition has many important practical applications, like surveillance and access control. It is concerned with the problem of correctly identifying face images and assigning them to persons in a database. This paper proposes using SIFT features [4] for the recognition process. The new technique is compared with well-established face recognition algorithms, namely Eigenfaces [7] and Fisherfaces [6, 2]. The results show the superiority of the new method over these two methods, specially using smaller training sets.
منابع مشابه
Feature Selection for Face Recognition Using a Genetic Algorithm
Face recognition has been one of the challenging problems of computer vision. In response to this problem, SIFT features [1] have been used in [2]. However, since SIFT features were addressed to object recognition; we need to select the features that best fits in the face recognition problem. So, in this paper, we are using a genetic algorithm to select the most important features for face reco...
متن کاملInvariant Local Features for Face Detection
In the domain of object recognition, the SIFT feature [1] is known to be a very successful local invariant feature. The performance of the recognition task using SIFT features is very robust and also can be done in real-time. This project present an approach that adopt the SIFT feature for the task of face detection. A feature database is created for the detection of generic face features and a...
متن کاملFace recognition using SURF features
The Scale Invariant Feature Transform (SIFT) proposed by David G. Lowe has been used in face recognition and proved to perform well. Recently, a new detector and descriptor, named Speed-Up Robust Features (SURF) suggested by Herbert Bay, attracts people’s attentions. SURF is a scale and in-plane rotation invariant detector and descriptor with comparable or even better performance with SIFT. Bec...
متن کاملLucas-Kanade Scale Invariant Feature Transform for Uncontrolled Viewpoint Face Recognition
Face recognition has been widely investigated in the last decade. However, real world application for face recognition is still a challenge. Most of these face recognition algorithms are under controlled settings, such as limited viewpoint and illumination changes. In this paper, we focus on face recognition which tolerates large viewpoint change. A novel framework named Lucas-Kanade Scale Inva...
متن کاملSIFT/LBP 3D face recognition
3D face recognition is a promising alternative to face the problem of recognizing 2D robustness. Therefore, the main advantage of 3D face recognition-based approach uses all the information on the geometry of the face, which allows us to get an accurate representation of the face. In the proposing contribution all distinctive facial features are captured by first extracting SIFT (Scale Invarian...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006