• 제목/요약/키워드: vector compression and expansion

검색결과 3건 처리시간 0.017초

Three-dimensional Face Recognition based on Feature Points Compression and Expansion

  • Yoon, Andy Kyung-yong;Park, Ki-cheul;Park, Sang-min;Oh, Duck-kyo;Cho, Hye-young;Jang, Jung-hyuk;Son, Byounghee
    • Journal of Multimedia Information System
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    • 제6권2호
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    • pp.91-98
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    • 2019
  • Many researchers have attempted to recognize three-dimensional faces using feature points extracted from two-dimensional facial photographs. However, due to the limit of flat photographs, it is very difficult to recognize faces rotated more than 15 degrees from original feature points extracted from the photographs. As such, it is difficult to create an algorithm to recognize faces in multiple angles. In this paper, it is proposed a new algorithm to recognize three-dimensional face recognition based on feature points extracted from a flat photograph. This method divides into six feature point vector zones on the face. Then, the vector value is compressed and expanded according to the rotation angle of the face to recognize the feature points of the face in a three-dimensional form. For this purpose, the average of the compressibility and the expansion rate of the face data of 100 persons by angle and face zone were obtained, and the face angle was estimated by calculating the distance between the middle of the forehead and the tail of the eye. As a result, very improved recognition performance was obtained at 30 degrees of rotated face angle.

세그먼트 차원압축을 이용한 HMM의 음절인식 (Syllable Recognition of HMM using Segment Dimension Compression)

  • 김주성;이양우;허강인;안점영
    • 한국음향학회지
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    • 제15권2호
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    • pp.40-48
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    • 1996
  • 본 논문은 단음절 전구간에 대해 4프레임폭과 7프레임폭을 결합하여 만든 40차원의 세그먼트를 K-L전개와 신경망으로 각각 10, 14, 20차원으로 압축하여 연속분포 HMM의 음성인식 특징파라미터로 사용하였다. 그리고 이산지속시간, 희귀계수 그리고 혼합분포를 특징 파라미터로 추가한 경우와 비교검토하였다. 단음절 100개에 대한 인식실험결과 연속분포 HMM의 인식률 85.19%에 비해 희귀계수를 부가한 경우 1.4%, 혼합분포를 이용한 경우 2.36%, 이산 지속시간제어를 한 경우 2.78%의 인식률이 향상되었다. 그리고 K-L전개에 의한 압축파라미터만 이용한 경우는 멜켑스트럼 + 희귀계수의 경우보다 인식률이 낮았으나, K-L전개에 의한 압축파라미터에 멜켑스트럼과 희귀계수를 부가한 경우는 동등한 결과를 얻을 수 있었다. 신경망에 의한 압축파라미터를 이용한 경우에는 비선형 변환인 시그모이드 함수를 사용하므로 음성의 동적변화가 잘 반영되어 K-L전개 및 다른 방법에 비해 향상된 인식결과를 얻을 수 있었다.

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Influence of infill walls on modal expansion of distribution of effective earthquake forces in RC frame structures

  • Ucar, Taner
    • Earthquakes and Structures
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    • 제18권4호
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    • pp.437-449
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    • 2020
  • It is quite apparent that engineering concerns related to the influence of masonry infills on seismic behavior of reinforced concrete (RC) structures is likely to remain relevant in the long term, as infill walls maintain their functionalities in construction practice. Within this framework, the present paper mainly deals with the issue in terms of modal expansion of effective earthquake forces and the resultant modal responses. An adequate determination of spatial distribution of effective earthquake forces over the height of the building is highly essential for both seismic analysis and design. The possible influence of infill walls is investigated by means of modal analyses of two-, three-, and four-bay RC frames with a number of stories ranging from 3 to 8. Both uniformly and non-uniformly infilled frames are considered in numerical analyses, where infill walls are simulated by adopting the model of equivalent compression strut. Consequently, spatial distribution of effective earthquake forces, modal static base shear force response of frames, modal responses of story shears from external excitation vector and lateral floor displacements are obtained. It is found that, infill walls and their arrangement over the height of the frame structure affect the spatial distribution of modal inertia forces, as well as the considered response quantities. Moreover, the amount of influence varies in stories, but is not very dependent to bay number of frames.