5605322
Multimodal Facial Gender and Ethnicity Identification
Human faces provide demographic information, such as gender and ethnicity. Different modalities of human faces, e.g., range and intensity, provide different cues for gender and ethnicity identifications. In this paper we exploit the range information of human faces for ethnicity identification using a support vector machine. An integration scheme is also proposed for ethnicity and gender identifications by combining the registered range and intensity images. The experiments are conducted on a database containing 1240 facial scans of 376 subjects. It is demonstrated that the range modality provides competitive discriminative power on ethnicity and gender identifications to the intensity modality. For both gender and ethnicity identifications, the proposed integration scheme outperforms each individual modality.
43527681
Learning-based pulmonary nodule detection from multislice CT data
176930
Face detection and synthesis using Markov random field models
Markov random fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray levels for images of human faces. These models are trained using data bases of face and non-face images. The trained MRF models are then used for detecting human faces in test images. We investigate the performance of the face detection algorithm for two classes of MRFs given by the first- and second-order neighborhood systems. From the cross validation results and from actual detection in real images, it is shown that the second-order model makes fewer false detections. We also investigate the possibility of increasing our training data base of faces by simulating face-like images from the trained MRFs. The performance of the re-trained MRFs based on added face-like images is compared to the original training data base.
121253028
Three-dimensional model based face recognition
The performance of face recognition systems that use two-dimensional (2D) images is dependent on consistent conditions such as lighting, pose and facial expression. We are developing a multi-view face recognition system that utilizes three-dimensional (3D) information about the face to make the system more robust to these variations. This work describes a procedure for constructing a database of 3D face models and matching this database to 2.5D face scans which are captured from different views, using coordinate system invariant properties of the facial surface. 2.5D is a simplified 3D (x, y, z) surface representation that contains at most one depth value (z direction) for every point in the (x, y) plane. A robust similarity metric is defined for matching, based on an iterative closest point (ICP) registration process. Results are given for matching a database of 18 3D face models with 113 2.5D face scans.
1730176
Integrating Range and Texture Information for 3D Face Recognition
The performance of face recognition systems that use two-dimensional images depends on consistent conditions w.r.t. lighting, pose, and facial appearance. We are developing a face recognition system that utilizes three-dimensional shape information to make the system more robust to arbitrary view, lighting, and facial appearance. For each subject, a 3D face model is constructed by integrating several 2.5D face scans from different viewpoints. A 2.5D scan is composed of one range image along with a registered 2D color image. The recognition engine consists of two components, surface matching and appearance-based matching. The surface matching component is based on a modified Iterative Closest Point (ICP) algorithm.The candidate list used for appearance matching is dynamically generated based on the output of the surface matching component, which reduces the complexity of the appearance-based matching stage. The 3D model in the gallery is used to synthesize new appearance samples with pose and illumination variations that are used for discriminant subspace analysis. The weighted sum rule is applied to combine the two matching components. A hierarchical matching structure is designed to further improve the system performance in both accuracy and efficiency. Experimental results are given for matching a database of 100 3D face models with 598 2.5D independent test scans acquired in different pose and lighting conditions, and with some smiling expression. The results show the feasibility of the proposed matching scheme.
7724153
Resampling for Face Recognition
A number of applications require robust human face recognition under varying environmental lighting conditions and different facial expressions, which considerably vary the appearance of human face. However, in many face recognition applications, only a small number of training samples for each subject are available; these samples are not able to capture all the facial appearance variations. We utilize the resampling techniques to generate several subsets of samples from the original training dataset. A classic appearance-based recognizer, LDA-based classifier, is applied to each of the generated subsets to construct a LDA representation for face recognition. The classification results from each subset are integrated by two strategies: majority voting and the sum rule. Experiments conducted on a face database containing 206 subjects (2,060 face images) show that the proposed approaches improve the recognition accuracy of the classical LDA-based face classifier by about 7 percentages.
10976624
On the maximum induced forests of a connected cubic graph without triangles
Let t(G) denote cardinality of a maximum induced forest of a graph G with n vertices. For connected simple cubic graphs G without triangles, it is shown that t(G)?2n3 except for two particular graphs. This lower bound is sharp and it improves a result due to J.A. Bondy, et al. 1]. Using this result, we show that Ewald Speckenmeyer's Conjecture, i.e. t(G)?2n3 for all biconnected cubic graphs G with girth 4, is true, except for two particular graphs, which we describe.
16545185
Hybrid Methods for POS Guessing of Chinese Unknown Words
This paper describes a hybrid model that combines a rule-based model with two statistical models for the task of POS guessing of Chinese unknown words. The rule-based model is sensitive to the type, length, and internal structure of unknown words, and the two statistical models utilize contextual information and the likelihood for a character to appear in a particular position of words of a particular length and POS category. By combining models that use different sources of information, the hybrid model achieves a precision of 89%, a significant improvement over the best result reported in previous studies, which was 69%.
12380989
Hamiltonian cycles in bipartite graphs
We give a sufficient condition for bipartite graphs to be Hamiltonian. The condition involves the edge-density and balanced independence number of a bipartite graph.
12662382
Autonomous rating oriented agent allocation to achieve high response in demand-oriented information service system
The efficient and reliable information service provision and utilization is an important infrastructure in the high-assurance information service system. In this paper, we introduce a rating oriented distributed information system sustained by push/pull mobile agents to cope with providers' and users' heterogeneous requirements. Based on this environment, autonomous information provision technology is proposed. However, when users' demand changes, congestion might arise in the system. In order to achieve load balancing for users' timeliness access and guarantee that users can always get the information from a certain pathway, autonomous information reallocation technology is proposed.
11665105
Agent-based autonomous information services integration and allocation to achieve high response and low cost in distributed information service system
The goal of autonomous information service integration is to enable information utilization opportunities far beyond those possible in a disconnected environment. We have proposed an agent-based distributed information service system architecture, called Faded Information Field (FIF) to cope with the rapidly evolving situations of providers' and users' heterogeneous requirements. In the case of a mono-service request, the system is designed to reduce the time needed for users to access the information and to preserve the consistency of the replicas. However, when the user requests joint selection of multiple services, synchronization of atomic actions and timeliness have to be assured by the system. The service-oriented autonomous integration and allocation for heterogeneous FIFs to provide one-stop service for users' multiservice requirements are proposed. Through the comparison simulation to conventional systems, the effectiveness of the proposed technology is proved.