• NEWSLETTER 전기공업
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• no.96-7 s.152
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• pp.2-11
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• 1996

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.660-662
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• 2023

3차원 포인트 클라우드의 의미적 분할은 환경을 구성하는 물체 단위로 포인트 클라우드를 분할하는 작업으로서, 환경의 3차원적 구성을 이해하고 환경과 상호작용에 필수적인 시각 지능을 요구한다. 본 논문에서는 포인트 클라우드에서 추출하는 3차원 기하학적 특징과 함께 멀티-뷰 영상에서 추출하는 2차원 시각적 특징들도 활용하는 새로운 3차원 포인트 클라우드 의미적 분할 모델 MFNet을 제안한다. 제안 모델은 서로 이질적인 2차원 시각적 특징과 3차원 기하학적 특징의 효과적인 융합을 위해, 새로운 중기 융합 전략과 멀티-모달 교차 주의집중을 이용한다. 본 논문에서는 ScanNetV2 벤치마크 데이터 집합을 이용한 다양한 실험들을 통해, 제안 모델 MFNet의 우수성을 입증한다.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Journal of Climate Change Research
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• v.2 no.2
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• pp.93-106
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• 2011

Republic of Korea officially announced its mid term reduction target which reduce about 30% of BAU GHG emission by 2020 in the 15th meeting of UNFCCC(COP 15) held in Copenhagen, Denmark 2009. To achieve this goal, it is necessary to understand the serious of climate change and take part in GHG reduction not only industry but also the nation. However, such positive participation in green life which may cause inconvenient of the life of the people. It should be accomplished with providing reliable information. This study suggests the scientific potentialities of GHG emission by guideline on low carbon life and green life to form and change a lifestyle suitable for coping with climate change. And also, this study quantitate the GHG reduction which may reduce demand for air conditioning by cool biz and warm biz. In Korea, this campaign has become known as 'CoolMaebsi' by Ministry of Environmental of Korea. 'CoolMaebsi' is a compound word of 'Cool' which means feel refreshed, and 'Maebsi' is a Korean word which means attire. Though this campaign is effective and significant to reduce the GHG emission yet there were no study on quantitative analysis. Therefore this study calculated reduced energy consumption and potential GHG emission by measuring variation of skin temperature. As the result, wearing warm biz and cool biz have an effect of reducing not only the energy consumption but also GHG emission. To achieve the low carbon society, it is necessary to improve the energy saving system and introduce the policy which guide to change a life style.