• Title/Summary/Keyword: 그림자데이터

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Hexagonal Grid Shadow Generation using Bézier Curves (베지어 곡선을 활용한 육각 그리드의 그림자 생성 방법)

  • Minseok Kim;Taekgwan Nam;Youngjin Park
    • Smart Media Journal
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    • v.12 no.4
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    • pp.47-57
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    • 2023
  • The hexagonal grid structure has been studied for processing and representing spatial information data in Geographic Information Systems. Visualization using a hexagonal grid has high visibility compared to other grid representation methods. However, it is difficult to effectively convey quantitative data and differences between grids depending on the geospatial data represented. In this paper, we propose a method to visually emphasize the hexagonal grid by generating shadow on the outside of the hexagonal grid. To do so, we offset the outer line segments of the hexagonal grid to be emphasized and generate a Bézier curve based on that information to determine the final shadow shape. We also apply variable transparency toward the edges of the shadow because the shadow gradually fades away from the hexagonal grid. We have shown that the proposed method can effectively generate shadow areas given not only a single hexagonal grid but also multiple hexagonal grids and can generate various shadow shapes based on user interface inputs. We apply the proposed method to Yongsan-gu, one of the districts of Seoul, and show the results of visually emphasizing it after generating shadow using the proposed method.

Real-Time Shadow Generation Using Image-Based Rendering Technique (영상기반 렌더링 기법을 이용한 실시간 그림자 생성 기법)

  • 이중연;임인성
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.628-630
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    • 2000
  • 3D 컴퓨터 그래픽스에서 그림자는 매우 중요한 요소이다. 그림자가 없으며 물체와 물체간의 정확한 위치를 파악하기가 어렵기 때문이다. 즉 물체가 다른 물체에 바로 붙어 있는지 조금 떨어져 있는지를 알아내기가 곤란한 것이다. 이러한 그림자의 중요성에도 불구하고 현존하는 3D 가속 하드웨어들은 그림자의 생성을 전혀 지원하지 못하고 있다. 또한, 이것을 보완하기 위해 많은 그림자 생성 알고리즘들이 제시되었지만 모두 그 한계가 명확하였다. 많은 그림자 생성 기법 중 텍스춰 하드웨어를 이용한 그림자 지도 기법은 광원과 물체가 고정되어 있을 경우 매우 빠른 속도로 그림자를 생성시킬 수 있지만 과원이나 물체가 움직일 경우에는 속도가 느려지게 된다. 본 논문에서는 그림자 지도 기법에 영상기반 렌더링 기법을 적용하여 실시간으로 그림자를 생성하고자 하였다. 본 논문의 기법은 매우 많은 메모리를 필요로 하기 때문에 데이터를 적당히 샘플링하여 웨이블릿 기반 압축 기법으로 압축하였고, 그림자를 생성할 때는 가장 가까운 저장된 그림자들을 2차원 보강하였다.

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Shadow Removal via Attention Mechanism and Recurrent Network (주의 매커니즘 기반 피드백 신경망을 이용한 그림자 제거 방법)

  • Kim, Minwoo;Kim, Wonjun
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • fall
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    • pp.161-163
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    • 2021
  • 대부분의 영상에 존재하는 그림자는 다양한 딥러닝 기반 영상처리 작업을 수행함에 방해가 되는 요소이다. 영상 내 그림자는 다양한 광원과 다양한 물체들의 상호작용에 의해 복잡하게 생성되며 이를 제거하는 것을 통해 다양한 Computer Vision task의 성능을 향상시킬 수 있다. 이 논문에서는 영상 내 그림자를 감지하여 Attention mechanism을 통해 그림자를 제거하고 Recurrent 하게 작업을 수행하며 복잡한 그림자를 단계적으로 제거하는 네트워크를 구현하였으며, Recurrent 한 네트워크에서 이전 단계의 데이터를 다음 단계에 효율적으로 전달하는 방식에 대한 실험을 수행하였다.

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Real-Time Shadow Generation Using Image-Based Rendering Technique (영상기반 렌더링 기법을 이용한 실시간 그림자 생성)

  • Lee, Jung-Yeon;Im, In-Seong
    • Journal of the Korea Computer Graphics Society
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    • v.7 no.1
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    • pp.27-35
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    • 2001
  • Shadows are important elements in producing a realistic image. In rendering. generation of the exact shape and position of shadow is crucial in providing the user with visual cues on the scene. While the shadow map technique quickly generates a shadow for the scene wherein objects and light sources are fixed. it gets slow down as they start to move. In this paper. we apply an image-based rendering technique to generate shadows in real-time using graphics hardware. Due to the heavy requirement of storage for a shadow map repository. we use a wavelet-based compression scheme for effective compression. Our method will be efficiently used in generating realistic scenes in many real-time applications such as 3D games and virtual reality systems.

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Consideration upon Importance of Metadata Extraction for a Hyper-Personalized Recommender System on Unsupervised Learning (비지도 학습 기반 초개인화 추천 서비스를 위한 메타데이터 추출의 중요성 고찰)

  • Paik, Juryon;Ko, Kwang-Ho
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.19-22
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    • 2022
  • 서비스 관점에서 구축되는 추천 시스템의 성능은 얼마나 효율적인 추천 모델을 적용하여 심층적으로 설계되었는가에 좌우된다고도 볼 수 있다. 특히, 추천 시스템의 초개인화는 세계적인 추세로 1~2년 전부터 구글, 아마존, 알리바바 등의 데이터 플랫폼 강자들이 경쟁적으로 딥 러닝 기반의 알고리즘을 개발, 자신들의 추천 서비스에 적용하고 있다. 본 연구는 갈수록 고도화되는 추천 시스템으로 인해 발생하는 여러 문제들 중 사용자 또는 서비스 정보가 부족하여 계속적으로 발생하고 있는 Cold-start 문제와 추천할 서비스와 사용자는 지속적으로 늘어나지만 실제로 사용자가 소비하게 되는 서비스의 비율은 현저하게 감소하는 데이터 희소성 문제 (Sparsity Problem)에 대한 솔루션을 모색하는 알고리즘 관점에서 연구하고자 한다. 본 논문은 첫 단계로, 적용하는 메타데이터에 따라 추천 결과의 정확성이 얼마나 차이가 나는지를 보이고 딥러닝 비지도학습 방식을 메타데이터 선정 및 추출에 적용하여 실시간으로 변화하는 소비자의 실제 생활 패턴 및 니즈를 예측해야 하는 필요성에 대해서 기술하고자 한다.

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Calculating the Sunlight Amount for Buildings Using SAS: A Case Study of Gyeongsan City (그림자 분석 시뮬레이션을 활용한 건축물별 일조량 산정 - 경산시를 사례로)

  • Kim, Do-Ryeong;Kim, Sung-Jae;Han, Soo-Hee;Jo, Myung-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.1
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    • pp.159-172
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    • 2014
  • As greenhouse gas emissions have been increasing in the world, global warming is being recognized as a cause of the global problems like climate change. This is closely associated the fossil fuels. Thus renewable energy has been brought to the attention of many people as the upcoming alternative energy source to cope with the fossil drain and increased environmental regulations. Especially, the solar energy among renewable energy has drastically increased. In this study, we calculate on daylight ratio about the solar energy for buildings based on digital surface model. The digital surface model was made using the spatial information data. And it was simulated the shadow analysis using SAS. Therefore, it was suitable places to utilize the solar energy in the Gyeongsan city. Consequently, the daylight ratio was considered important factor to select region of the industry of the solar light power generation.

Shadow Generation By Extracted Point data on Subregion (영역별 데이터 추출에의한 효과적인 그림자 표현)

  • Ko, Chan;Kang, Jung-Ho
    • Journal of the Korea Computer Industry Society
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    • v.3 no.2
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    • pp.217-226
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    • 2002
  • To describe an object realistically is the most important thing in the 3-dimentional space in computer graphics. It is not enough with one or two factors. Several factors should be considered such as perspective sense, cubic effect, material of an object, shadow, strength of light, etc. A shadow algorithm plays an important part in the realistic description of an object. There are many methods to describe a shadow, but it means numerous repeated operations to describe a shadow and it needs much time. We seperate the shadow part and calculate the strength of light for numerous points and it takes much time. This thesis presents a new method to describe a shadow quickly by separating categories maintaining a realistic description of an object.

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Shadow Removal based on the Deep Neural Network Using Self Attention Distillation (자기 주의 증류를 이용한 심층 신경망 기반의 그림자 제거)

  • Kim, Jinhee;Kim, Wonjun
    • Journal of Broadcast Engineering
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    • v.26 no.4
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    • pp.419-428
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    • 2021
  • Shadow removal plays a key role for the pre-processing of image processing techniques such as object tracking and detection. With the advances of image recognition based on deep convolution neural networks, researches for shadow removal have been actively conducted. In this paper, we propose a novel method for shadow removal, which utilizes self attention distillation to extract semantic features. The proposed method gradually refines results of shadow detection, which are extracted from each layer of the proposed network, via top-down distillation. Specifically, the training procedure can be efficiently performed by learning the contextual information for shadow removal without shadow masks. Experimental results on various datasets show the effectiveness of the proposed method for shadow removal under real world environments.

Efficient Learning and Classification for Vehicle Type using Moving Cast Shadow Elimination in Vehicle Surveillance Video (차량 감시영상에서 그림자 제거를 통한 효율적인 차종의 학습 및 분류)

  • Shin, Wook-Sun;Lee, Chang-Hoon
    • The KIPS Transactions:PartB
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    • v.15B no.1
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    • pp.1-8
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    • 2008
  • Generally, moving objects in surveillance video are extracted by background subtraction or frame difference method. However, moving cast shadows on object distort extracted figures which cause serious detection problems. Especially, analyzing vehicle information in video frames from a fixed surveillance camera on road, we obtain inaccurate results by shadow which vehicle causes. So, Shadow Elimination is essential to extract right objects from frames in surveillance video. And we use shadow removal algorithm for vehicle classification. In our paper, as we suppress moving cast shadow in object, we efficiently discriminate vehicle types. After we fit new object of shadow-removed object as three dimension object, we use extracted attributes for supervised learning to classify vehicle types. In experiment, we use 3 learning methods {IBL, C4.5, NN(Neural Network)} so that we evaluate the result of vehicle classification by shadow elimination.

CNN-based Shadow Detection Method using Height map in 3D Virtual City Model (3차원 가상도시 모델에서 높이맵을 이용한 CNN 기반의 그림자 탐지방법)

  • Yoon, Hee Jin;Kim, Ju Wan;Jang, In Sung;Lee, Byung-Dai;Kim, Nam-Gi
    • Journal of Internet Computing and Services
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    • v.20 no.6
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    • pp.55-63
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    • 2019
  • Recently, the use of real-world image data has been increasing to express realistic virtual environments in various application fields such as education, manufacturing, and construction. In particular, with increasing interest in digital twins like smart cities, realistic 3D urban models are being built using real-world images, such as aerial images. However, the captured aerial image includes shadows from the sun, and the 3D city model including the shadows has a problem of distorting and expressing information to the user. Many studies have been conducted to remove the shadow, but it is recognized as a challenging problem that is still difficult to solve. In this paper, we construct a virtual environment dataset including the height map of buildings using 3D spatial information provided by VWorld, and We propose a new shadow detection method using height map and deep learning. According to the experimental results, We can observed that the shadow detection error rate is reduced when using the height map.