• 제목/요약/키워드: descriptors

검색결과 506건 처리시간 0.027초

Silhouette differences among cats do not suggest a general selection for paedomorphosis

  • Pares-Casanova, Pere M.
    • 대한수의학회지
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    • 제53권3호
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    • pp.155-158
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    • 2013
  • Paedomorphosis is the retention of juvenile morphology at maturity and is important in generating evolutionary change in domestic species and species in the wild. This preliminary study compared morphological characteristics of seven domestic cat pure breeds and felid species from around the world. An original procedure based on elliptical Fourier (EF) methods was applied to head lateral views of specimens and were assessed in order to analyse head profile. For comparative purposes three domestic kittens of different ages and three species of genus Lynx were also used. EF descriptors, allowed for the quantification of the head profile. Using the Fourier transform, reconstruction of the mean head profile revealed that there was a general shape difference between wild cats, domestic cats and kittens. Results suggested that variability in head profile differentiate quite well between adult cats and kittens, but domestic and wild cats appeared grouped into a similar cluster. The similarity between breeds can thus be attributed more to the general head profile than to flatness, i.e. to the general conformation rather than facial profile. Therefore, no effect of paedomorphism on the studied breeds can be undertaken. The present approach opens interesting ethnological perspectives for the aloidic characterisation for domestic breeds.

3D Shape Descriptor for Segmenting Point Cloud Data

  • Park, So Young;Yoo, Eun Jin;Lee, Dong-Cheon;Lee, Yong Wook
    • 한국측량학회지
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    • 제30권6_2호
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    • pp.643-651
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    • 2012
  • Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

A Comparative QSPR Study of Alkanes with the Help of Computational Chemistry

  • Kumar, Srivastava Hemant
    • Bulletin of the Korean Chemical Society
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    • 제30권1호
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    • pp.67-76
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    • 2009
  • The development of a variety of methods like AM1, PM3, PM5 and DFT now allows the calculation of atomic and molecular properties with high precision as well as the treatment of large molecules with predictive power. In this paper, these methods have been used to calculate a number of quantum chemical descriptors (like Klopman atomic softness in terms of $E_n^{\ddag}\;and\;E_m^{\ddag}$, chemical hardness, global softness, electronegativity, chemical potential, electrophilicity index, heat of formation, total energy etc.) for 75 alkanes to predict their boiling point values. The 3D modeling, geometry optimization and semiempirical & DFT calculations of all the alkanes have been made with the help of CAChe software. The calculated quantum chemical descriptors have been correlated with observed boiling point by using multiple linear regression (MLR) analysis. The predicted values of boiling point are very close to the observed values. The values of correlation coefficient ($r^2$) and cross validation coefficient ($r_{cv}^2$) also indicates the generated QSPR models are valuable and the comparison of all the methods indicate that the DFT method is most reliable while the addition of Klopman atomic softness $E_n^{\ddag}$ in DFT method improves the result and provides best correlation.

디스크립터의 의미기술로서 정의를 통한 애매성 제거 (The Ambiguity Exclusion Using Definitions as Meaning Description of Descriptors)

  • 김지훈
    • 정보관리연구
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    • 제36권3호
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    • pp.97-126
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    • 2005
  • 지금까지 대부분의 시소러스에서 용어의 의미는 주로 관계나 범위주기를 통해 간접적으로 제시되어 왔다. 그러나 시소러스가 양적으로 팽창해짐에 따라, 이들을 통해 용어의 의미를 명확히 파악하는 것이 점차 어렵게 되었다. 이에 일부 시소러스는 사전의 정의를 함께 수록하기도 하였지만, 그 내용이나 형식이 만족스럽지 않은 것으로 인식되어 왔다. 이 연구는 용어의 의미를 제공하는 정의의 필요성을 토대로 표준화된 정의를 시소러스에 통합해 봄으로써, 시소러스가 더욱 발전할 수 있는 가능성을 제시하였다.

Video Representation via Fusion of Static and Motion Features Applied to Human Activity Recognition

  • Arif, Sheeraz;Wang, Jing;Fei, Zesong;Hussain, Fida
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권7호
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    • pp.3599-3619
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    • 2019
  • In human activity recognition system both static and motion information play crucial role for efficient and competitive results. Most of the existing methods are insufficient to extract video features and unable to investigate the level of contribution of both (Static and Motion) components. Our work highlights this problem and proposes Static-Motion fused features descriptor (SMFD), which intelligently leverages both static and motion features in the form of descriptor. First, static features are learned by two-stream 3D convolutional neural network. Second, trajectories are extracted by tracking key points and only those trajectories have been selected which are located in central region of the original video frame in order to to reduce irrelevant background trajectories as well computational complexity. Then, shape and motion descriptors are obtained along with key points by using SIFT flow. Next, cholesky transformation is introduced to fuse static and motion feature vectors to guarantee the equal contribution of all descriptors. Finally, Long Short-Term Memory (LSTM) network is utilized to discover long-term temporal dependencies and final prediction. To confirm the effectiveness of the proposed approach, extensive experiments have been conducted on three well-known datasets i.e. UCF101, HMDB51 and YouTube. Findings shows that the resulting recognition system is on par with state-of-the-art methods.

텍스처 기술자들을 이용한 이질적 얼굴 인식 시스템 (Heterogeneous Face Recognition Using Texture feature descriptors)

  • 배한별;이상윤
    • 한국정보전자통신기술학회논문지
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    • 제14권3호
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    • pp.208-214
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    • 2021
  • 최근 많은 지능형 보안 시나리오 및 범죄수사에서는 사진이 아닌 얼굴 영상과 다수의 정면 사진과의 매칭을 요구한다. 기존의 얼굴 인식 시스템은 이러한 요구를 충분히 충족시킬 수 없다. 본 논문에서는 동일 인물의 스케치와 사진 간의 양식 차이를 줄임으로써, 이질적 얼굴 인식 시스템의 성능을 향상시키는 알고리즘을 제안한다. 제안하는 알고리즘은 텍스처 기술자들(그레이 레벨 동시 발생 행렬, 멀티스케일 지역 이진 패턴)을 통하여 영상의 텍스처 특징들을 각각 추출하고, 이를 바탕으로 고유특징 정규화 및 추출기법을 통해 변환 행렬을 생성하게 된다. 이렇게 생성된 벡터들 간 계산된 스코어 값은 스코어 정규화 방식들을 통하여 최종적으로 스케치 영상의 신원을 인식하게 된다.

Incorporating Recognition in Catfish Counting Algorithm Using Artificial Neural Network and Geometry

  • Aliyu, Ibrahim;Gana, Kolo Jonathan;Musa, Aibinu Abiodun;Adegboye, Mutiu Adesina;Lim, Chang Gyoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권12호
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    • pp.4866-4888
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    • 2020
  • One major and time-consuming task in fish production is obtaining an accurate estimate of the number of fish produced. In most Nigerian farms, fish counting is performed manually. Digital image processing (DIP) is an inexpensive solution, but its accuracy is affected by noise, overlapping fish, and interfering objects. This study developed a catfish recognition and counting algorithm that introduces detection before counting and consists of six steps: image acquisition, pre-processing, segmentation, feature extraction, recognition, and counting. Images were acquired and pre-processed. The segmentation was performed by applying three methods: image binarization using Otsu thresholding, morphological operations using fill hole, dilation, and opening operations, and boundary segmentation using edge detection. The boundary features were extracted using a chain code algorithm and Fourier descriptors (CH-FD), which were used to train an artificial neural network (ANN) to perform the recognition. The new counting approach, based on the geometry of the fish, was applied to determine the number of fish and was found to be suitable for counting fish of any size and handling overlap. The accuracies of the segmentation algorithm, boundary pixel and Fourier descriptors (BD-FD), and the proposed CH-FD method were 90.34%, 96.6%, and 100% respectively. The proposed counting algorithm demonstrated 100% accuracy.

Phenotypic Characterization of Amaranth Resources for the Selection of Promising Materials

  • Hwang Bae Sohn;Su Jeong Kim;Jung Hwan Nam;Do Yeon Kim;Jong Nam Lee;Su Young Hong;Yul Ho Kim
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2022년도 추계학술대회
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    • pp.211-211
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    • 2022
  • Amaranth is a nutritious and broadly adapted seed crop in high demand around the world. A preliminary approach for understanding the genetics of amaranth resources entails a morphologic characterization, which can provide the basis for breeding the first variety in Korea, leading to satisfying the needs of farmers and consumers. Therefore, this study aimed to evaluate the phenotypic characteristics of ten genetic amaranth accessions for the selection of outstanding accessions in terms of yield and grain quality. A randomized complete block design was used, with fifteen replications for each accession under field conditions. Five quantitative and three qualitative descriptors were evaluated with descriptive analysis. The results showed that the accessions with plant heights smaller than the average (>112.7 cm) presented lower yields and smaller seed sizes, thus decreasing the grain quality. The cluster analyses established groups of accessions with good yields (>30.1 g of seeds per plant) and stable morphological characteristics. Based on yield and morphological descriptors, the proposed selection index indicated four accessions as potential parents for amaranth breeding programs in Kora.

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음성정보 내용분석을 통한 골프 동영상에서의 선수별 이벤트 구간 검색 (Retrieval of Player Event in Golf Videos Using Spoken Content Analysis)

  • 김형국
    • 한국음향학회지
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    • 제28권7호
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    • pp.674-679
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    • 2009
  • 본 논문은 골프 동영상에 포함된 오디오 정보로부터 검출된 이벤트 사운드 구간과 골프 선수이름이 포함된 음성구간을 결합하여 선수별 이벤트 구간을 검색하는 방식을 제안한다. 전체적인 시스템은 동영상으로부터 분할된 오디오 스트림으로부터 잡음제거, 오디오 구간분할, 음성 인식 등의 과정을 통한 자동색인 모듈과 사용자가 텍스트로 입력한 선수 이름을 발음열로 변환하고, 색인된 데이터베이스에서 질의된 선수 이름과 상응하는 음성구간과 연결되는 이벤트 구간을 찾아주는 검색 모듈로 구성된다. 선수이름 검색을 위해서 본 논문에서는 음소 기반, 단어 기반, 단어와 음소를 결합한 하이브리드 방식을 적용한 선수별 이벤트 구간 검색결과를 비교하였다.

시공간 2D 특징 설명자를 사용한 BOF 방식의 동작인식 (BoF based Action Recognition using Spatio-Temporal 2D Descriptor)

  • 김진옥
    • 인터넷정보학회논문지
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    • 제16권3호
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    • pp.21-32
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    • 2015
  • 동작인식 연구에서 비디오를 표현하는 시공간 부분 특징이 모델 없는 상향식 방식의 주요 주제가 되면서 동작 특징을 검출하고 표현하는 방법이 여러 연구를 통해 다양하게 제안되고 있다. 그 중에서 BoF(bag of features)방식은 가장 일관성 있는 인식 결과를 보여주고 있다. 비디오의 동작을 BoF로 나타내기 위해서는 어떻게 동작의 역동적 정보를 표현할 것인가가 가장 중요한 부분이다. 그래서 기존 연구에서는 비디오를 시공간 볼륨으로 간주하고 3D 동작 특징점 주변의 볼륨 패치를 복잡하게 설명하는 것이 가장 일반적인 방법이다. 본 연구에서는 기존 3D 기반 방식을 간략화하여 비디오의 동작을 BoF로 표현할 때 비디오에서 2D 특징점을 직접 수집하는 방식을 제안한다. 제안 방식의 기본 아이디어는 일반적 공간프레임의 2D xy 평면뿐만 아니라 시공간 프레임으로 불리는 시간축 평면에서 동작 특징점을 추출하여 표현하는 것으로 특징점이 비디오에서 역동적 동작 정보를 포착하기 때문에 동작 표현 특징 설명자를 3D로 확장할 필요 없이 2D 설명자만으로 간단하게 동작인식이 가능하다. SIFT, SURF 특징 표현 설명자로 표현하는 시공간 BoF 방식을 주요 동작인식 데이터에 적용하여 우수한 동작 인식율을 보였다. 3D기반의 HoG/HoF 설명자와 비교한 경우에도 제안 방식이 더 계산하기 쉽고 단순하게 이해할 수 있다.