• 한국항행학회논문지
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• 제15권5호
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• pp.696-704
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• 2011

본 논문에서는 단일 카메라와 초음파센서 데이터를 융합하는 이동 로봇 주행제어 알고리즘을 제안하였다. 이진화 영상처리를 위한 임계값을 영상 정보와 초음파센서 정보를 이용하는 퍼지추론기법으로 설정하였다. 임계값을 상황에 따라 가변하면 조도가 낮은 환경에서도 장애물 인식이 향상된다. 카메라 영상 정보와 초음파 센서 정보를 융합하여 장애물에 대한 격자지도를 생성하고 원궤적 경로기법으로 장애물을 회피하도록 한다. 제안된 알고리즘의 성능을 입증하기 위하여 조도가 낮은 실내와 좁은 복도에서 Pioneer 2-DX 이동로봇의 주행제어에 적용하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.308-320
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• 2016

Although the face almost always has an axisymmetric structure, it is generally not symmetrical image for the face image. However, the mirror image of the face image can reflect possible variation of the poses and illumination opposite to that of the original face image. A robust minimum squared error classification (RMSEC) algorithm is proposed in this paper. Concretely speaking, the original training samples and the mirror images of the original samples are taken to form a new training set, and the generated training set is used to perform the modified minimum sqreared error classification(MMSEC) algorithm. The extensive experiments show that the accuracy rate of the proposed RMSEC is greatly increased, and the the proposed RMSEC is not sensitive to the variations of the parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권7호
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• pp.1705-1720
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• 2013

Human face gender recognition requires fast image processing with high accuracy. Existing face gender recognition methods used traditional local features and machine learning methods have shortcomings of low accuracy or slow speed. In this paper, a new framework for face gender recognition to reach fast face gender recognition is proposed, which is based on Local Ternary Pattern (LTP) and Extreme Learning Machine (ELM). LTP is a generalization of Local Binary Pattern (LBP) that is in the presence of monotonic illumination variations on a face image, and has high discriminative power for texture classification. It is also more discriminate and less sensitive to noise in uniform regions. On the other hand, ELM is a new learning algorithm for generalizing single hidden layer feed forward networks without tuning parameters. The main advantages of ELM are the less stringent optimization constraints, faster operations, easy implementation, and usually improved generalization performance. The experimental results on public databases show that, in comparisons with existing algorithms, the proposed method has higher precision and better generalization performance at extremely fast learning speed.

• 로봇학회논문지
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• 제4권1호
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• pp.25-33
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• 2009

One of the main problems of topological localization in a real indoor environment is variations in the environment caused by dynamic objects and changes in illumination. Another problem arises from the sense of topological localization itself. Thus, a robot must be able to recognize observations at slightly different positions and angles within a certain topological location as identical in terms of topological localization. In this paper, a possible solution to these problems is addressed in the domain of global topological localization for mobile robots, in which environments are represented by their visual appearance. Our approach is formulated on the basis of a probabilistic model called the Bayes filter. Here, marginalization of dynamics in the environment, marginalization of viewpoint changes in a topological location, and fusion of multiple visual features are employed to measure observations reliably, and action-based view transition model and action-associated topological map are used to predict the next state. We performed experiments to demonstrate the validity of our proposed approach among several standard approaches in the field of topological localization. The results clearly demonstrated the value of our approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2075-2092
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• 2017

Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.

• 한국산학기술학회논문지
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• 제8권3호
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• pp.620-626
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• 2007

본 연구는 셋백에 관한 예비조사를 통하여 셋백의 정의와 셋백발생의 배경 및 기능 등을 파악하고 셋백 사례들에 대한 분석의 틀을 물리적인 특성, 주요 발생 요인, 그리고 셋백유형의 세 가지 범주로 나누어 각 범주별 분석 항목들과 산정식들을 제시함으로써 셋백에 관한 분석의 체계를 마련하고자 하였다. 또한 이를 서울지역 초고층 주거건물의 사례들에 적용하여 기존 사례들에서 이루어진 셋백의 특징들과 한계점을 제시하였다.

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

• 한국통신학회논문지
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• 제34권3C호
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• pp.268-273
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• 2009

홍채 인식은 홍채 패턴 정보를 이용하여 사람의 신원을 확인하는 생체 인식 기술이다. 이러한 홍채 인식 시스템에 있어 조명의 영향이나 동공의 크기, 머리의 기울어짐 등으로 인해 발생될 수 있는 홍채 패턴의 변화에 대해 무관한 특징을 추출하는 것은 중요한 과제이다. 본 논문에서는 국부적 방향 히스토그램을 이용해 조명의 변화나 홍채의 회전에 강인한 홍채인식 방법을 제안하였다. 제안된 방법은 특징 추출 및 특징 비교 시 회전에 대해 별도의 처리가 필요하지 않아 고속의 특징 추출 및 특징 비교가 가능하며 성능도 기존의 방법과 대등함을 실험을 통하여 확인하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.156-158
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• 2007

The radiance observed from the ocean depends on the illumination and viewing geometry along with the water properties, and this variation is called the bidirectional effect which is important to be considered in ocean color remote sensing. In the present study, as a preliminary step, the spectral-angular radiances in coastal water were investigated with experiments for a range of viewing geometric conditions $(0-70^{\circ})$. Over a phytoplankton-dominated water surface the upward radiance for visible and near-infrared wavelengths (example, SeaWiFS and GOCI) increased at nadir and decreased toward the near-horizon, becoming dependent of viewing angles (with higher radiance at nadir view angle and lower radiance at near-horizon viewing angle). This variations were better expressed by the Q-factor, which relates upwelling radiance to the upwelling irradiance (i.e., $Q=E_u/L_u$, also dependent on Sun's position). The Q-factor for this case was more non-uniform with the considered wavelengths and was dependent on viewing geometric conditions. These experimental results confirm the previous similar findings in other coastal waters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4502-4518
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• 2015

Fisher linear discriminant analysis (LDA) is one of the most popular projection techniques for feature extraction and has been widely applied in face recognition. However, it cannot be used when encountering the single sample per person problem (SSPP) because the intra-class variations cannot be evaluated. In this paper, we propose a novel method called local similarity based linear discriminant analysis (LS_LDA) to solve this problem. Motivated by the "divide-conquer" strategy, we first divide the face into local blocks, and classify each local block, and then integrate all the classification results to make final decision. To make LDA feasible for SSPP problem, we further divide each block into overlapped patches and assume that these patches are from the same class. To improve the robustness of LS_LDA to outliers, we further propose local similarity based median discriminant analysis (LS_MDA), which uses class median vector to estimate the class population mean in LDA modeling. Experimental results on three popular databases show that our methods not only generalize well SSPP problem but also have strong robustness to expression, illumination, occlusion and time variation.