• 제목/요약/키워드: Multi-Temporal

검색결과 671건 처리시간 0.035초

다중 시구간 신경회로망을 이용한 인간 행동 인식 (Human Activity Recognition using Multi-temporal Neural Networks)

  • 이현진
    • 디지털콘텐츠학회 논문지
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    • 제18권3호
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    • pp.559-565
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    • 2017
  • 스마트폰에 내장된 가속도 센서를 이용하여 사용자의 동작 상태나 행동을 인식하기 위한 연구가 다양하게 진행되어 왔다. 본 논문에서는 스마트폰의 3D 가속도 정보에 신경회로망을 적용하여 사람의 행동을 인식하는 연구를 진행하였다. 시계열 데이터를 신경회로망에 그대로 적용하면 성능상의 문제가 발생한다. 따라서 여러 시구간에 대해 특징을 추출하여 각 시구간에 대해 신경회로망을 학습시키고, 이 신경회로망들의 출력들을 입력으로 하여 학습하여 구성하는 다중 시구간 신경회로망을 제안하였다. 제안하는 방법을 실제 가속도 데이터에 적용한 결과 SVM, AdaBoost, IBk 등 다른 분류기보다 우수한 성능을 보였다.

Comparison of Three Land Cover Classification Algorithms -ISODATA, SMA, and SOM - for the Monitoring of North Korea with MODIS Multi-temporal Data

  • Kim, Do-Hyung;Jeong, Seung-Gyu;Park, Chong-Hwa
    • 대한원격탐사학회지
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    • 제23권3호
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    • pp.181-188
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    • 2007
  • The objective of this research was to investigate the optimal land cover classification algorithm for the monitoring of North Korea with MODIS multi-temporal data based on monthly phenological characteristics. Three frequently used land cover classification algorithms, ISODATA1), SMA2), and SOM3) were employed for this study; the land cover categories were forest, grass, agricultural, wetland, barren, built-up, and water body. The outcomes of the study can be summarized as follows. First, the overall classification accuracy of ISODATA, SMA, and SOM was 69.03%, 64.28%, and 73.57%, respectively. Second, ISODATA and SMA resulted in a higher classification accuracy of forest and agricultural categories, but SOM performed better for the built-up area, bare soil, grassland, and water. A possible explanation for this difference would be related to the difference of sensitivity against the vegetation activity. This would be related to the capability of SOM to express all of their values without any loss of data by maintaining the topology between pixels of primitive data after classification, while ISODATA and SMA retain limited amount of data after normalization process. Third, we can conclude that SOM is the best algorithm for monitoring the land cover change of North Korea.

Multi-scale and Interactive Visual Analysis of Public Bicycle System

  • Shi, Xiaoying;Wang, Yang;Lv, Fanshun;Yang, Xiaohang;Fang, Qiming;Zhang, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권6호
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    • pp.3037-3054
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    • 2019
  • Public bicycle system (PBS) is a new emerging and popular mode of public transportation. PBS data can be adopted to analyze human movement patterns. Previous work usually focused on specific scales, and the relationships between different levels of hierarchies are ignored. In this paper, we introduce a multi-scale and interactive visual analytics system to investigate human cycling movement and PBS usage condition. The system supports level-of-detail explorative analysis of spatio-temporal characteristics in PBS. Visual views are designed from global, regional and microcosmic scales. For the regional scale, a bicycle network is constructed to model PBS data, and an flow-based community detection algorithm is applied on the bicycle network to determine station clusters. In contrast to the previous used Louvain algorithm, our method avoids producing super-communities and generates better results. We provide two cases to demonstrate how our system can help analysts explore the overall cycling condition in the city and spatio-temporal aggregation of stations.

Mapping Paddy Rice Varieties Using Multi-temporal RADARSAT SAR Images

  • Jang, Min-Won;Kim, Yi-Hyun;Park, No-Wook;Hong, Suk-Young
    • 대한원격탐사학회지
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    • 제28권6호
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    • pp.653-660
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    • 2012
  • This study classified paddy fields according to rice varieties and monitored temporal changes in rice growth using SAR backscatter coefficients (${\sigma}^{\circ}$). A growing period time-series of backscatter coefficients was set up for nine fine-beam mode RADARSAT-1 SAR images from April to October 2005. The images were compared with field-measured rice growth parameters such as leaf area index (LAI), plant height, fresh and dry biomass, and water content in grain and plants for 45 parcels in Dangjin-gun, Chungnam Province, South Korea. The average backscatter coefficients for early-maturing rice varieties (13 parcels) ranged from -18.17 dB to -6.06 dB and were lower than those for medium-late maturing rice varieties during most of the growing season. Both crops showed the highest backscatter coefficient values at the heading stage (late July) for early-maturing rice, and the difference was greatest before harvest for early-maturing rice. The temporal difference in backscatter coefficients between rice varieties may play a key role in identifying early-maturing rice fields. On the other hand, comparisons with field-measured parameters of rice growth showed that backscatter coefficients decreased or remained on a plateau after the heading stage, even though the growth of the rice canopy had advanced.

다중 배경모델과 순시적 중앙값 배경모델을 이용한 불안정 상태 카메라로부터의 실시간 이동물체 검출 (Real-Time Detection of Moving Objects from Shaking Camera Based on the Multiple Background Model and Temporal Median Background Model)

  • 김태호;조강현
    • 제어로봇시스템학회논문지
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    • 제16권3호
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    • pp.269-276
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    • 2010
  • In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.

RapidEye영상과 선형분광혼합화소분석 기법을 이용한 낙동강 유역의 클로로필-a 농도 추정 (Estimating Chlorophyll-a Concentration using Spectral Mixture Analysis from RapidEye Imagery in Nak-dong River Basin)

  • 이혁;남기범;강태구;윤승준
    • 한국물환경학회지
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    • 제30권3호
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    • pp.329-339
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    • 2014
  • This study aims to estimate chlorophyll-a concentration in rivers using multi-spectral RapidEye imagery and Spectral Mixture Analysis (SMA) and assess the applicability of SMA for multi-temporal imagery analysis. Comparison between images (acquired on Oct. and Nov., 2013) predicted and ground reference chlorophyll-a concentration showed significant performance statistically with determination coefficients of 0.49 and 0.51, respectively. Two band (Red-RE) model for the October and November 2013 RapidEye images showed low performance with coefficient of determinations ($R^2$) of 0.26 and 0.16, respectively. Also Three band (Red-RE-NIR) model showed different performance with $R^2$ of 0.016 and 0.304, respectively. SMA derived Chlorophyll-a concentrations showed relatively higher accuracy than band ratio models based values. SMA was the most appropriate method to calculate Chlorophyll-a concentration using images which were acquired on period of low Chlorophyll-a concentrations. The results of SMA for multi-temporal imagery showed low performance because of the spatio-temporal variation of each end members. This approach provides the potential of providing a cost effective method of monitoring river water quality and management using multi-spectral imagery. In addition, the calculated Chlorophyll-a concentrations using multi-spectral RapidEye imagery can be applied to water quality modeling, enhancing the predicting accuracy.

Lateral Brow Lift: A Multi-Point Suture Fixation Technique

  • Foustanos, Andreas;Drimouras, Georgios;Panagiotopoulos, Konstantinos
    • Archives of Plastic Surgery
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    • 제42권5호
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    • pp.580-587
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    • 2015
  • Background Descent of the lateral aspect of the brow is one of the earliest signs of aging. The purpose of this study was to describe an open surgical technique for lateral brow lifts, with the goal of achieving reliable, predictable, and long-lasting results. Methods An incision was made behind and parallel to the temporal hairline, and then extended deeper through the temporoparietal fascia to the level of the deep temporal fascia. Dissection was continued anteriorly on the surface of the deep temporal fascia and subperiosteally beyond the temporal crest, to the level of the superolateral orbital rim. Fixation of the lateral brow and tightening of the orbicularis oculi muscle was achieved with the placement of sutures that secured the tissue directly to the galea aponeurotica on the lateral aspect of the incision. An additional fixation was made between the temporoparietal fascia and the deep temporal fascia, as well as between the temporoparietal fascia and the galea aponeurotica. The excess skin in the temporal area was excised and the incision was closed. Results A total of 519 patients were included in the study. Satisfactory lateral brow elevation was obtained in most of the patients (94.41%). The following complications were observed: total relapse (n=8), partial relapse (n=21), neurapraxia of the frontal branch of the facial nerve (n=5), and limited alopecia in the temporal incision (n=9). Conclusions We consider this approach to be a safe and effective procedure, with long-lasting results.

시공간 적응적인 예측에 기초한 다시점 위너-지브 비디오 부호화 기법 (Multi-View Wyner-Ziv Video Coding Based on Spatio-temporal Adaptive Estimation)

  • 이범용;김진수
    • 한국콘텐츠학회논문지
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    • 제16권6호
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    • pp.9-18
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    • 2016
  • 본 논문에서는 시공간 적응적인 예측에 기초한 다시점 위너-지브 비디오 부호화 기법을 제안한다. 제안하는 알고리즘은 기존 움직임 추정 방법을 보완하여 가중치를 부여한 결합 양방향 움직임 추정을 수행하고, 각 시점 영상의 에지 검출 및 합성을 통해 관심영역을 효과적으로 분류하여 움직임 벡터 분석을 통해 최종 참조 프레임을 선택하여 보간 한다. 제안하는 알고리즘은 단일 시점 내의 움직임 정보와 인접 카메라 프레임의 정보를 적응적으로 이용함으로써 영상 내 다양한 폐색, 반사 영역에 대해 효율적으로 처리하고 더 나은 성능을 갖는다. 다양한 다시점 영상 시퀀스에 대한 실험을 통하여, 제안하는 알고리즘은 보조정보 생성하는 기존 알고리즘에 비해 평균 비트율 감소와 더불어 우수한 객관적 화질 향상을 얻었다.