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.
62601340
Deformation Modeling for Robust 3D Face Matching
Human face recognition based on 3D surface matching is promising for overcoming the limitations of current 2D image-based face recognition systems. The 3D shape is invariant to the pose and lighting changes, but not invariant to the non-rigid facial movement, such as expressions. Collecting and storing multiple templates for each subject in a large database (associated with various expressions) is not practical. We present a facial surface modeling and matching scheme to match 2.5D test scans in the presence of both non-rigid deformations and large pose changes (multiview) to a neutral expression 3D face model. A geodesic-based resampling approach is applied to extract landmarks for modeling facial surface deformations. We are able to synthesize the deformation learned from a small group of subjects (control group) onto a 3D neutral model (not in the control group), resulting in a deformed template. A personspecific (3D) deformable model is built for each subject in the gallery w.r.t. the control group by combining the templates with synthesized deformations. By fitting this generative deformable model to a test scan, the proposed approach is able to handle expressions and large pose changes simultaneously. Experimental results demonstrate that the proposed matching scheme based on deformation modeling improves the matching accuracy.
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.
18993736
Matching 2.5D Scans for Face Recognition
The performance of face recognition systems that use two-dimensional images is dependent on consistent conditions such as lighting, pose, and facial appearance. We are developing a face recognition system that uses three-dimensional depth information to make the system more robust to these arbitrary conditions. We have developed a face matching system that automatically correlates points in three dimensions between two 2.5D range images of different views. A hybrid Iterative Closest Point (ICP) scheme is proposed to integrate two classical ICP algorithms for fine registration of the two scans. A robust similarity metric is defined for matching purpose. Results are provided on a preliminary database of 10 subjects (one training image per subject) containing frontal face images of neutral expression with a testing database of 63 scans that varied in pose, expression and lighting.
43527681
Learning-based pulmonary nodule detection from multislice CT data
19393995
Skilled Forgery Detection in On-Line Signatures: A Multimodal Approach
Signature recognition has a long history of usage in authentication of transactions and legal contracts and hence is easily accepted by users in a variety of applications. However, the problem of skilled forgeries is an important challenge that needs to be overcome before signature recognition systems will become viable in unsupervised authentication systems. In this paper, we present a multimodal approach to forgery detection, where a physiological trait, the face of the signing person, is used to validate the signature. Methods of normalizing and combining the matching scores from the individual modalities are investigated. Test results of the system on a database of 100 users is presented. The system achieves an equal error rate of 2.2% in the presence of high quality skilled forgeries and could detect all the skilled forgeries at a genuine acceptance rate of 75%.
28342911
A matching game
Abstract We consider the following 2-person game playing on K n,n . Two players, maker and breaker, alternately take a previously untaken edge from K n,n , the complete bipartite graph of order 2 n . The game continues until all the edges of K n,n have been taken. Then the edges taken by maker induce a subgraph of K n,n , which is denoted by G ( M ). At the end of the game, we calculate the number of edge-disjoint perfect matchings of G ( M ), and denote this number by m ( M ). The maker's aim is to make this number big and the breaker's is to force it small. We will prove the following result: For any given η >0, there exists N ( η ), such that if n ⩾ N ( η ), then maker has a strategy to guarantee m(M)⩾( 1 2 −η)n .
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.
20901797
Decentralized workload management for assurance according to heterogeneous service levels
Due to the advent of electronic commerce, the service provider can offer the customer a Service Level Agreement (SLA) to distinguish itself in today's competitive market. Different users require different levels of service in terms of information consumption or response time, appearing a need of a system able to assure the heterogeneous service levels of the users in such a mission-critical environment. In this paper, we propose an information service infrastructure based on the Faded Information Field (FIF), a distributed service replica network founded on push/pull mobile agent technology. The cooperation between the autonomous agents and the nodes allows the online maintenance and auto-reconstruction of the FIF system in order to satisfy the different timely requirements of each user even in an ever-changing environment. Moreover, the system is able to provide different maximum information volume according to the user's service level, a double-sided feature that benefits to both the provider's business strategy and the differentiated timeliness access technology presented on this paper. The effectiveness of the proposed technology has been proved through evaluation and the simulation results show that the system is able to adapt and satisfy the different requirements of timeliness and the different levels of information volume required by each user under changing workloads, compared with conventional systems.
14843520
Deriving knowledge from figures for digital libraries
Figures in digital documents contain important information. Current digital libraries do not summarize and index information available within figures for document retrieval. We present our system on automatic categorization of figures and extraction of data from 2-D plots. A machine-learning based method is used to categorize figures into a set of predefined types based on image features. An automated algorithm is designed to extract data values from solid line curves in 2-D plots. The semantic type of figures and extracted data values from 2-D plots can be integrated with textual information within documents to provide more effective document retrieval services for digital library users. Experimental evaluation has demonstrated that our system can produce results suitable for real-world use.
6155777
Claws contained in all n-tournaments
Abstract We prove that any claw of order n with degree d≤ 3 8 n is n-unavoidable, which means that any tournament of order n contains it as a subdigraph. A simple corollary is that any tournament has a directed Hamiltonian path.