• Title/Summary/Keyword: Digital Image of Time Series

Search Result 40, Processing Time 0.022 seconds

A Case Study on Morten Lasskogen's Cloud Series - Based on 3ds Max and Unreal Engine Technology -

  • JinXuan Zhao;Xinyi Shan;Jeanhun Chung
    • International journal of advanced smart convergence
    • /
    • v.12 no.2
    • /
    • pp.96-101
    • /
    • 2023
  • Digital art creation has become an indispensable part of today's society, but traditional digital art production methods have been difficult to meet the growing creative needs of artists. Therefore, this study takes the cloud series works of artist Morten Lasskogen as an example and explores the application value of 3D Max and Unreal Engine in digital art created by analyzing the lighting effects in the works of art. This research aims to form reference materials through actual case analysis and provide artists with more efficient ideas for digital art creation.

Adaptive Reconstruction of Harmonic Time Series Using Point-Jacobian Iteration MAP Estimation and Dynamic Compositing: Simulation Study

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
    • /
    • v.24 no.1
    • /
    • pp.79-89
    • /
    • 2008
  • Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series contaminated by noises resulted from mechanical problems or sensing environmental condition. There is also a high likelihood that during the data acquisition periods the target site corresponding to any given pixel may be covered by fog or cloud, thereby resulting in bad or missing observation. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. A feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. The experimental results of this simulation study show the potentiality of the proposed system to reconstruct the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather. This study provides fundamental information on the elements of the proposed system for right usage in application.

Adaptive Reconstruction of NDVI Image Time Series for Monitoring Vegetation Changes (지표면 식생 변화 감시를 위한 NDVI 영상자료 시계열 시리즈의 적응 재구축)

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
    • /
    • v.25 no.2
    • /
    • pp.95-105
    • /
    • 2009
  • Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

Visual Location Recognition Using Time-Series Streetview Database (시계열 스트리트뷰 데이터베이스를 이용한 시각적 위치 인식 알고리즘)

  • Park, Chun-Su;Choeh, Joon-Yeon
    • Journal of the Semiconductor & Display Technology
    • /
    • v.18 no.4
    • /
    • pp.57-61
    • /
    • 2019
  • Nowadays, portable digital cameras such as smart phone cameras are being popularly used for entertainment and visual information recording. Given a database of geo-tagged images, a visual location recognition system can determine the place depicted in a query photo. One of the most common visual location recognition approaches is the bag-of-words method where local image features are clustered into visual words. In this paper, we propose a new bag-of-words-based visual location recognition algorithm using time-series streetview database. The proposed algorithm selects only a small subset of image features which will be used in image retrieval process. By reducing the number of features to be used, the proposed algorithm can reduce the memory requirement of the image database and accelerate the retrieval process.

Tool Fracture Detection Using System Identification (시스템인식을 이용한 공구파손 검출)

  • 사승윤
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
    • /
    • 1996.03a
    • /
    • pp.119-123
    • /
    • 1996
  • The demands for robotic and automatic system are continually increasing in manufacturing fields. There were so many studies to monitor and predict system, but it were mainly relied upon measuring of cutting force, current of motor spindle and using acoustic sensor, etc. In this study digital image of time series sequence was acquired taking advantage of optical technique. Then, mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR model was selected for system model, fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, we found there was a system stability.

  • PDF

A Study on Measurement of Repetitive Work using Digital Image Processing (영상처리를 이용한 반복적 작업의 측정에 관한 연구)

  • Lee, Jeong-Cheol;Sim, Eok-Su;Kim, Nam-Joo;Park, Chan-Kwon;Park, Jin-Woo
    • IE interfaces
    • /
    • v.14 no.1
    • /
    • pp.95-105
    • /
    • 2001
  • Previous work measurement methods need much time and effort of time study analysts because they have to measure required time through direct observations. In this study, we propose a method which efficiently measures standard times without involvement of human analysts using digital image processing techniques. This method consists of two main steps: motion representation step and cycle segmentation step. In motion representation step, we first detect the motion of any object distinct from its background by differencing two consecutive images separated by a constant time interval. The images thus obtained then pass through an edge detector filter. Finally, the mean values of coordinates of significant pixels of the edge image are obtained. Through these processes, the motions of the observed worker are represented by two time series data of worker location in horizontal and vertical axes. In the second step, called the cycle segmentation step, we extract the frames which have maximum or minimum coordinates in one cycle and store them in a stack, and calculate each cycle time using these frames. In this step we also consider methods on how to detect work delays due to unexpected events such as operator's escapement from the work area, or interruptions. To condude, the experimental results show that the proposed method is very cost-effective and useful for measuring time standards for various work environment.

  • PDF

Research Trends Analysis of Machine Learning and Deep Learning: Focused on the Topic Modeling (머신러닝 및 딥러닝 연구동향 분석: 토픽모델링을 중심으로)

  • Kim, Chang-Sik;Kim, Namgyu;Kwahk, Kee-Young
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.15 no.2
    • /
    • pp.19-28
    • /
    • 2019
  • The purpose of this study is to examine the trends on machine learning and deep learning research in the published journals from the Web of Science Database. To achieve the study purpose, we used the abstracts of 20,664 articles published between 1990 and 2017, which include the word 'machine learning', 'deep learning', and 'artificial neural network' in their titles. Twenty major research topics were identified from topic modeling analysis and they were inclusive of classification accuracy, machine learning, optimization problem, time series model, temperature flow, engine variable, neuron layer, spectrum sample, image feature, strength property, extreme machine learning, control system, energy power, cancer patient, descriptor compound, fault diagnosis, soil map, concentration removal, protein gene, and job problem. The analysis of the time-series linear regression showed that all identified topics in machine learning research were 'hot' ones.

A Study on the Tool Fracture Detection Algorithm Using System Identification (시스템인식을 이용한 공구파손검출 알고리듬에 관한 연구)

  • Sa, Seung-Yun;Yu, Eun-Lee;Ryu, Bong-Hwan
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.21 no.6
    • /
    • pp.988-994
    • /
    • 1997
  • The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc. In this study, digital image of time series sequence was acquired by taking advantage of optical technique. Mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR(auto regressive) model was selected for system model and fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, it was found that there was a system stability.

The Analysis of Temporal and Spatial Variation on the Vegetation Area of the Siwha Tidat Flat (시화 갯벌식생범위의 시-공간적 변이 분석)

  • Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
    • /
    • v.20 no.3
    • /
    • pp.349-356
    • /
    • 2011
  • This research is aim to analyze of changing landscape and according to phenological cycle from image information of coastal environment obtained by multi-media were analyzed by camera and satellite image. The digital camera and satellite image were used for tidal flat vegetation monitoring during the construction of Sihwa lake. The vegetation type and phenological cycle of Sihwa tidal flat have been changed with the Sihwa lake ecosystem. The environment changes of Sihwa tidal flat area and ecological change were analyzed by field work digital camera images and satellite images. The airborne, UAV and satellite images were classified with the changed elements of coastal ecological environment and tidal flat vegetation monitoring carried out the changed area and shape of vegetation distribution with time series images.

Real-time Interactive Particle-art with Human Motion Based on Computer Vision Techniques (컴퓨터 비전 기술을 활용한 관객의 움직임과 상호작용이 가능한 실시간 파티클 아트)

  • Jo, Ik Hyun;Park, Geo Tae;Jung, Soon Ki
    • Journal of Korea Multimedia Society
    • /
    • v.21 no.1
    • /
    • pp.51-60
    • /
    • 2018
  • We present a real-time interactive particle-art with human motion based on computer vision techniques. We used computer vision techniques to reduce the number of equipments that required for media art appreciations. We analyze pros and cons of various computer vision methods that can adapted to interactive digital media art. In our system, background subtraction is applied to search an audience. The audience image is changed into particles with grid cells. Optical flow is used to detect the motion of the audience and create particle effects. Also we define a virtual button for interaction. This paper introduces a series of computer vision modules to build the interactive digital media art contents which can be easily configurated with a camera sensor.