• 제목/요약/키워드: descriptors

검색결과 505건 처리시간 0.028초

마커리스 트래킹을 위한 특징 서술자의 데이터베이스 생성 및 검색방법 (A Database Creation and Retrival Method of Feature Descriptors for Markerless Tracking)

  • 윤요섭;김태영
    • 한국게임학회 논문지
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    • 제11권3호
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    • pp.63-72
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    • 2011
  • 본 논문에서는 증강 현실 환경에서 실시간 마커리스 트래킹을 수행하기 위한 특징 서술자 데이터베이스 생성 및 검색 방법을 제안한다. 먼저, 특징 서술자를 효율적으로 검색하기 위하여 특징 서술자의 형태를 기준으로 정수 부호화 하여 총 4 단계의 인덱스 데이터베이스를 구성한다. 특정 특징 서술자의 검색은 데이터베이스에서 각 단계별로 유사성 있는 후보 특징 서술자의 인덱스를 탐색하고 입력된 특징 서술자와 탐색된 모든 후보 특징 서술자들의 유클리드 거리 값 비교를 통해 이루어진다. 본 연구에서 제안한 검색방법은 형태를 기반으로 유사하지 않은 특징 서술자들을 검색 대상에서 제외하여 검색의 효율을 높였다. 제안된 방법은 기존 KD-Tree 방법에 비해서 특징 서술자당 약 16ms의 검색 속도 개선이 있었음을 확인할 수 있었다.

DETECTION OF FRUITS ON NATURAL BACKGROUND

  • Limsiroratana, Somchai;Ikeda, Yoshio;Morio, Yoshinari
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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    • pp.279-286
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    • 2000
  • The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

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사용자 피드백 기반의 적응적 가중치를 이용한 정지영상 검색 (Image Retrieval using Adaptable Weighting Scheme on Relevance Feedback)

  • 이진수;김현준;윤경로;이희연
    • 방송공학회논문지
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    • 제5권1호
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    • pp.61-67
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    • 2000
  • 사용자 피드백은 일반적으로 사용자가 의도하는 정지영상 검색 조건을 기술하는 데만 주로 사용되어 왔다. 그러나, 본 논문에서는 사용자 피드백을 정지영상의 특징을 기술하는데 사용함으로써 사용자에 의존적이지 않은 정지영상 검색에 적용하였다. 그리고 본 논문에서는 사용자 피드백을 사용하여 각 정지영상마다 고유한 특징을 반영하도록 특징 정보와 관련된 가중치를 전문가에 비중을 두어 학습시킴으로써, 일반적인 검색 성능을 향상시킬 수 있다. 이러한 시스템을 구축하기 위해 본 논문에서는 칼라 기술자와 텍스쳐 기술자를 기반으로 한 전역 특징 정보와 지역 특징 정보, 그리고 각 기술자들간의 가중치와 기술자 내의 요소 가중치로 구성된 정지영상 기술 구조를 제안하고, 또한 잘못된 학습을 방지하기 위해 신뢰도에 기반한 가중치 학습 방법을 소개한다.

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RLDB: Robust Local Difference Binary Descriptor with Integrated Learning-based Optimization

  • Sun, Huitao;Li, Muguo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권9호
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    • pp.4429-4447
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    • 2018
  • Local binary descriptors are well-suited for many real-time and/or large-scale computer vision applications, while their low computational complexity is usually accompanied by the limitation of performance. In this paper, we propose a new optimization framework, RLDB (Robust-LDB), to improve a typical region-based binary descriptor LDB (local difference binary) and maintain its computational simplicity. RLDB extends the multi-feature strategy of LDB and applies a more complete region-comparing configuration. A cascade bit selection method is utilized to select the more representative patterns from massive comparison pairs and an online learning strategy further optimizes descriptor for each specific patch separately. They both incorporate LDP (linear discriminant projections) principle to jointly guarantee the robustness and distinctiveness of the features from various scales. Experimental results demonstrate that this integrated learning framework significantly enhances LDB. The improved descriptor achieves a performance comparable to floating-point descriptors on many benchmarks and retains a high computing speed similar to most binary descriptors, which better satisfies the demands of applications.

Image Registration Based On Statistical Descriptors In Frequency Domain

  • Chang, Min-hyuk;Ahmad, Muhammad-Bilal;Lee, Cheul-hee;Chun, Jong-hoon;Park, Seung-jin;Park, Jong-an
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -3
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    • pp.1531-1534
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    • 2002
  • Shape description and its corresponding matching algorithm is one of the main concerns in MPEG-7. In this paper, a new method is proposed for shape registration of 2D objects for MPEG-7 Shapes are recognized using the Hu statistical moments in frequency domain. The Hu moments are moment-based descriptors of planar shapes, which are invariant under general translation, rotational, scaling, and reflection transformation. The image is transformed into frequency domain using Fourier Transform. Annular and radial wedge distributions fur the power spectra are extracted. Different statistical features (Hu moments) are found f3r the power spectrum of each selected transformed individual feature. The Euclidean distance of the extracted moment descriptors of the features are found with respect to the shapes in the database. The minimum Euclidean distance is the candidate for the matched shape. The simulation results are performed on the test shapes of MPEG-7.

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A DFT and QSAR Study of Several Sulfonamide Derivatives in Gas and Solvent

  • Abadi, Robabeh Sayyadi kord;Alizadehdakhel, Asghar;Paskiabei, Soghra Tajadodi
    • 대한화학회지
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    • 제60권4호
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    • pp.225-234
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    • 2016
  • The activity of 34 sulfonamide derivatives has been estimated by means of multiple linear regression (MLR), artificial neural network (ANN), simulated annealing (SA) and genetic algorithm (GA) techniques. These models were also utilized to select the most efficient subsets of descriptors in a cross-validation procedure for non-linear -log (IC50) prediction. The results obtained using GA-ANN were compared with MLR-MLR, MLR-ANN, SA-ANN and GA-ANN approaches. A high predictive ability was observed for the MLR-MLR, MLR-ANN, SA-ANN and MLR-GA models, with root mean sum square errors (RMSE) of 0.3958, 0.1006, 0.0359, 0.0326 and 0.0282 in gas phase and 0.2871, 0.0475, 0.0268, 0.0376 and 0.0097 in solvent, respectively (N=34). The results obtained using the GA-ANN method indicated that the activity of derivatives of sulfonamides depends on different parameters including DP03, BID, AAC, RDF035v, JGI9, TIE, R7e+, BELM6 descriptors in gas phase and Mor 32u, ESpm03d, RDF070v, ATS8m, MATS2e and R4p, L1u and R3m in solvent. In conclusion, the comparison of the quality of the ANN with different MLR models showed that ANN has a better predictive ability.

Graphemes Segmentation for Arabic Online Handwriting Modeling

  • Boubaker, Houcine;Tagougui, Najiba;El Abed, Haikal;Kherallah, Monji;Alimi, Adel M.
    • Journal of Information Processing Systems
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    • 제10권4호
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    • pp.503-522
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    • 2014
  • In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

Convolutional Neural Network Based Multi-feature Fusion for Non-rigid 3D Model Retrieval

  • Zeng, Hui;Liu, Yanrong;Li, Siqi;Che, JianYong;Wang, Xiuqing
    • Journal of Information Processing Systems
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    • 제14권1호
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    • pp.176-190
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    • 2018
  • This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

Person-Independent Facial Expression Recognition with Histograms of Prominent Edge Directions

  • Makhmudkhujaev, Farkhod;Iqbal, Md Tauhid Bin;Arefin, Md Rifat;Ryu, Byungyong;Chae, Oksam
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권12호
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    • pp.6000-6017
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    • 2018
  • This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.

MPEG-7 시각 정보 기술자의 인덱싱 및 결합 알고리즘 (Algorithms for Indexing and Integrating MPEG-7 Visual Descriptors)

  • 송치일;낭종호
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제34권1호
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    • pp.1-10
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    • 2007
  • 본 논문에서는 MPEG-7 시각 정보 기술자인 Dominant Color와 Contour Shape 기술자에 대한 새로운 인덱싱 알고리즘을 제안한다. Dominant Color 기술자에서 사용되는 비교 연산 식은 가우스 혼합 모델에 기초하고 있기 때문에 기술자의 각 속성들을 하나의 칼라 히스토그램 형태로 변형시켜서 인덱스로 사용한다. Contour Shape 기술자는 두 단계 형태의 알고리즘을 사용하는데, 첫 번째 단계에서는 글로벌 변수인 Eccentricity와 Circularity를 사용한 대략적인 비교를 통해서 비슷하지 않은 이미지 오브젝트를 배제시키고 두 번째 단계에서 남겨진 오브젝트들과 질의 오브젝트들간의 Peak 변수를 사용한 비교 연산을 통해 인덱싱을 수행한다. 또한 본 논문은 효율적인 멀티미디어 데이타 검색을 위해서 두 가지의 MPEG-7 시각 정보 기술자 결합 알고리즘을 제안한다. 첫 번째 결합 알고리즘은 가중치를 확률로 변환해서 반영하는 것이고 두 번째는 가중치를 각 비교 연산 결과값의 중요도로 간주하는 방법이다. 실험을 통해서 결과를 분석해 보면 근사화를 통한 인덱스 생성으로 100%의 정확도를 유지 할 수는 없지만 논문에서 제안된 각 기술자의 인덱싱 알고리즘과 기술자들의 결합 알고리즘은 기본 검색 알고리즘과 비교했을 때 매우 빠른 속도 향상을 보여주었다. 본 논문에서 제안된 알고리즘은 MPEG-7을 사용하는 검색 시스템의 데이타베이스 구축에 효율적으로 사용될 수 있다.