The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In many identification problems, finding a duplicate using biometrics is very challenging task because of the size of the database and the errors related to the core biometrics engine. Fusion of different modes of biometric system can lead to improved recognition accuracy. In a multi classifier fusion scenario, the confidence of one classifier should not only depend on its own decision confidence...
The matrix based data representation has been recognized to be effective for face recognition because it can deal with the undersampled problem. One of the most popular algorithms, the two dimensional linear discriminant analysis (2DLDA), has been identified to be effective to encode the discriminative information for training matrix represented samples. However, 2DLDA does not converge in the training...
Face detection plays an important role in many vision applications. Since Viola and Jones proposed the first real-time AdaBoost based object detection system, much effort has been spent on improving the boosting method. In this work, we first show that feature selection methods other than boosting can also be used for training an efficient object detector. In particular, we have adopted greedy sparse...
In view of the training time-consuming shortcoming of the conventional AdaBoost algorithm in face detection, in this paper, a new algorithm was presented combining effectively the optimizing rect-features and weak classifier learning algorithm, which can largely improve the hit-rate and decrease the train time. Optimized rect-feature means that when searching rect-feature we can establish a growth...
This paper proposes a pain expression recognition method using boosted Gabor features. At first, each neonatal facial image which is normalized to the size of 112times92 pixels is convoluted with the 2D Gabor filters to extract 412160 Gabor features. Since the high-dimensional Gabor feature vectors are quite redundant, we propose a modified version of AdaBoost algorithm, called the HybridBoost, to...
Facial expressions are considered a critical factor in neonatal pain assessment. This paper proposes a pain expression recognition method using boosted Gabor features. Each neonatal facial image is convoluted with the 2D Gabor filters to extract 412,160 Gabor features. Since the high-dimension Gabor feature vectors are quite redundant, we employs a modified version of AdaBoost algorithm to select...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.