• Title/Summary/Keyword: Spatio-temporal image

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A Fast Block Motion Estimation Algorithm Based On Motion Classification And Directional Search Patterns (움직임 분류와 직접 탐색 패턴을 통한 고속 블록 움직임 추정 알고리즘)

  • Park, Soon-Chul;Nisar, Humaira;Choi, Tae-Sun
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.903-904
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    • 2008
  • This paper suggests a simple scheme of block motion estimation in which the search pattern selection is based on the classification of motion content available in the spatio temporal neighboring blocks. The search area is divided into eight sectors and the search pattern selection is also based on the direction of predicted motion vector. Experimental results show that the proposed algorithm has achieved good predicted image quality measured in terms of PSNR and has very less computational complexity.

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Motion Boundary Detection and Motion Vector Estimation by spatio-temporal Gradient Method using a New Spatial Gradient (새로운 공간경사를 사용한 시공간 경사법에 의한 운동경계 검출 및 이동벡터 추정)

  • 김이한;김성대
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.2
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    • pp.59-68
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    • 1993
  • The motion vector estimation and motion boundary detection have been briskly studied since they are an important clue for analysis of object structure and 3-d motion. The purpose of this researches is more exact estimation, but there are two main causes to make inaccurate. The one is the erroneous measurement of gradients in brightness values and the other is the blurring of motion boundries which is caused by the smoothness constraint. In this paper, we analyze the gradient measurement error of conventional methods and propose new technique based on it. When the proposed method is applied to the motion boundary detection in Schunck and motion vector estimation in Horn & Schunck, it is shown to have much better performance than conventional method is some artificial and real image sequences.

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X-ray Medical Image Spatio-temporal Denoising Algorithm (엑스선 의료영상의 시공간 잡음제거 알고리즘)

  • Park, Sangwook;Joo, Hui Jin;Sohn, Jeongwoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2016.10a
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    • pp.685-686
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    • 2016
  • 엑스선 투시촬영장치와 같은 의료용 동영상의 잡음 제거에 있어서 시공간 잡음제거 알고리즘을 제안한다. 제안된 알고리즘에서는 무한 충격 응답 기반 시간 영역 잡음 제거 얄고리즘을 도입하여 움직임이 적은 영역에서는 자연스러운 잡음 제거가 가능하며 움직임이 많은 영역에서는 연산량 측면에서 효율성을 고려하여 지역적 평균 필터 기반 공간 잡음 제거 알고리즘을 적용하여 움직임에 의한 흐려짐 열화 현상을 최소화 하면서 잡음 제거를 수행하였다.

Dynamic PIV Measurement of Swirl Flow in a PC Fan

  • ARAMAKI Shinichiro;HAYAMI Hiroshi
    • 한국가시화정보학회:학술대회논문집
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    • 2004.12a
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    • pp.41-45
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    • 2004
  • The dynamic particle image velocimetry (PIV) is consisted of a high frequency pulse laser, high speed cameras and a timing controller. The three velocity components of flow downstream of an axial flow fan for PC cooling system are measured using the dynamic PIV system. An Axial flow fan has seven blades of 72 mm in diameter. The rotating speed is 1800 rpm. The downstream flow is visualized by smoke particles of about $0.3-1\;{\mu}m$ in diameter. The three-dimensional instantaneous velocity fields are measured at three downstream planes. The swirl velocity component was diffused downstream and the change in time-mean vorticity distribution downstream was also discussed. The spatio-temporal change in axial velocity component with the blades passing is recognized by the instantaneous vector maps. And the dynamic behavior of vorticity moving with the rotating blades is discussed using the unsteady vorticity maps.

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Video Saliency Detection Using Bi-directional LSTM

  • Chi, Yang;Li, Jinjiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.6
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    • pp.2444-2463
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    • 2020
  • Significant detection of video can more rationally allocate computing resources and reduce the amount of computation to improve accuracy. Deep learning can extract the edge features of the image, providing technical support for video saliency. This paper proposes a new detection method. We combine the Convolutional Neural Network (CNN) and the Deep Bidirectional LSTM Network (DB-LSTM) to learn the spatio-temporal features by exploring the object motion information and object motion information to generate video. A continuous frame of significant images. We also analyzed the sample database and found that human attention and significant conversion are time-dependent, so we also considered the significance detection of video cross-frame. Finally, experiments show that our method is superior to other advanced methods.

Impact Assessment of Forest Development on Net Primary Production using Satellite Image Spatial-temporal Fusion and CASA-Model (위성영상 시공간 융합과 CASA 모형을 활용한 산지 개발사업의 식생 순일차생산량에 대한 영향 평가)

  • Jin, Yi-Hua;Zhu, Jing-Rong;Sung, Sun-Yong;Lee, Dong-Ku
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.20 no.4
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    • pp.29-42
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    • 2017
  • As the "Guidelines for GHG Environmental Assessment" was revised, it pointed out that the developers should evaluate GHG sequestration and storage of the developing site. However, the current guidelines only taking into account the quantitative reduction lost within the development site, and did not consider the qualitative decrease in the carbon sequestration capacity of forest edge produced by developments. In order to assess the quantitative and qualitative effects of vegetation carbon uptake, the CASA-NPP model and satellite image spatial-temporal fusion were used to estimate the annual net primary production in 2005 and 2015. The development projects between 2006 and 2014 were examined for evaluate quantitative changes in development site and qualitative changes in surroundings by development types. The RMSE value of the satellite image fusion results is less than 0.1 and approaches 0, and the correlation coefficient is more than 0.6, which shows relatively high prediction accuracy. The NPP estimation results range from 0 to $1335.53g\;C/m^2$ year before development and from 0 to $1333.77g\;C/m^2$ year after development. As a result of analyzing NPP reduction amount within the development area by type of forest development, the difference is not significant by type of development but it shows the lowest change in the sports facilities development. It was also found that the vegetation was most affected by the edge vegetation of industrial development. This suggests that the industrial development causes additional development in the surrounding area and indirectly influences the carbon sequestration function of edge vegetaion due to the increase of the edge and influx of disturbed species. The NPP calculation method and results presented in this study can be applied to quantitative and qualitative impact assessment of before and after development, and it can be applied to policies related to greenhouse gas in environmental impact assessment.

An Optimal Selection of Frame Skip and Spatial Quantization for Low Bit Rate Video Coding (저속 영상부호화를 위한 최적 프레임 율과 공간 양자화 결정)

  • Bu, So-Young;Lee, Byung-Uk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.6C
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    • pp.842-847
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    • 2004
  • We present a new video coding technique to tradeoff frame rate and picture quality for low bit rate video coding. We show a model equation for selecting the optimal frame rate from the motion content of the source video. We can determine DCT quantization parameter (QP) using the frame rate and bit rate. For objective video quality measurement we propose a simple and effective error measure for skipped frames. The proposed method enhances the video quality up to 2 ㏈ over the H.263 TMN5 encoder.

Secured Authentication through Integration of Gait and Footprint for Human Identification

  • Murukesh, C.;Thanushkodi, K.;Padmanabhan, Preethi;Feroze, Naina Mohamed D.
    • Journal of Electrical Engineering and Technology
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    • v.9 no.6
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    • pp.2118-2125
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    • 2014
  • Gait Recognition is a new technique to identify the people by the way they walk. Human gait is a spatio-temporal phenomenon that typifies the motion characteristics of an individual. The proposed method makes a simple but efficient attempt to gait recognition. For each video file, spatial silhouettes of a walker are extracted by an improved background subtraction procedure using Gaussian Mixture Model (GMM). Here GMM is used as a parametric probability density function represented as a weighted sum of Gaussian component densities. Then, the relevant features are extracted from the silhouette tracked from the given video file using the Principal Component Analysis (PCA) method. The Fisher Linear Discriminant Analysis (FLDA) classifier is used in the classification of dimensional reduced image derived by the PCA method for gait recognition. Although gait images can be easily acquired, the gait recognition is affected by clothes, shoes, carrying status and specific physical condition of an individual. To overcome this problem, it is combined with footprint as a multimodal biometric system. The minutiae is extracted from the footprint and then fused with silhouette image using the Discrete Stationary Wavelet Transform (DSWT). The experimental result shows that the efficiency of proposed fusion algorithm works well and attains better result while comparing with other fusion schemes.

A Study of Spring Drought Using Terra MODIS Satellite Image - For the Soyanggang Dam Watershed - (Terra MODIS 위성영상을 이용한 봄 가뭄 연구 - 소양강댐유역을 대상으로 -)

  • SHIN, Hyung-Jin;PARK, Min-Ji;HWANG, Eui-Ho;CHAE, Hyo-Sok;PARK, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.4
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    • pp.145-157
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    • 2015
  • In 2015, drought was at the worst stage of devastation in Soyanggang Dam watershed. The purpose of this study is to trace the drought area around Soyanggang dam watershed by using Terra MODIS image because it has the ability of spatio-temporal dynamics. The MODIS indices, which included the enhanced vegetation index (NDVI), were extracted from MODIS product MOD13 16-day composite datasets with a spatial resolution of 250m from 2010.01.01 to 2015.06.30. We found that application of Vegetation Condition Index (VCI) and Standardized Vegetation Index (SVI) was suitable for monitoring the drought area. The result can be used to acquire the drought data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of drought effects.

Adaptive V1-MT model for motion perception

  • Li, Shuai;Fan, Xiaoguang;Xu, Yuelei;Huang, Jinke
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.371-384
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    • 2019
  • Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.