• Journal of Information Processing Systems
• /
• 제12권3호
• /
• pp.468-488
• /
• 2016

The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

• 스마트미디어저널
• /
• 제8권1호
• /
• pp.43-50
• /
• 2019

수많은 디바이스들이 무선 네트워크를 통해 연결 되고 있고, 이러한 연결을 효율적으로하기 위한 연구들이 진행되고 있다. 많은 연구에서 효율적인 디바이스 관리를 위해 클러스터링을 사용하고 있지만 클러스터의 특정 노드에 부하가 집중되는 경우가 많아 전체 네트워크가 불안정해질 수 있다. 이러한 문제를 해결하기 위해 본 논문에서는 센서 노드의 효율적인 관리를 위해 중앙 집중식 불균등 체인 클러스터 스케줄링 모델을 제안한다. 클러스터의 구성을 위해 클러스터 헤드 범위와 기지국까지의 거리를 기반으로 하고, 기지국의 위치가 동일하지 않은 동심 체인 클러스터링을 구축하기 위해 주벡터 투사 기법을 사용한다. 데이터의 전송은 다중 무선 액세스 인터페이스인 MIMO(Multiple-Input Multiple-Output)를 활용한다. 실험을 통해 클러스터 헤드의 에너지 소비를 줄이고 네트워크 수명이 향상됨을 보인다.

• 제어로봇시스템학회논문지
• /
• 제20권8호
• /
• pp.875-881
• /
• 2014

The redundancy resolution of the seven DOF (Degree of Freedom) upper limb exoskeleton is key to the synchronous motion between a robot and a human user. According to the seven DOF human arm model, positioning and orientating the wrist can be completed by multiple arm configurations that results in the non-unique solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and its effect on the redundancy resolution of the seven DOF human arm model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing two cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid of the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each of two consecutive points along the task space trajectory. The contribution of each criterion on the redundancy was verified by the post processing of experimental data collected with a motion capture system. Results indicate that the bimodal redundancy resolution approach improved the accuracy of the predicted swivel angle. Statistical testing of the dynamic constraint contribution shows that under moderate speeds and no load, the dynamic component of the human arm is not dominant, and it is enough to resolve the redundancy without dynamic constraint for the realtime application.