A Combined Model of Outline Feature Map and CNN for Detection of People at the Beach 


Vol. 46,  No. 1, pp. 31-38, Jan.  2019
10.5626/JOK.2019.46.1.31


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  Abstract

As water safety accidents occur every year, many intelligent video surveillance systems are being developed to prevent water safety accidents. In this paper, we propose InsightCNN to accurately detect moving objects in complex images, such as beaches, in intelligent video surveillance systems. First, a basic model was constructed using 1x1 Convolution of Fully Convolutional Network and Residual Block of ResNet. We added an outline feature map that shows a key feature of the image, to the initial layer of the basic model. Results of the experiment demonstrate superiority of the idea of InsightCNN.


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  Cite this article

[IEEE Style]

G. Moon and Y. Kim, "A Combined Model of Outline Feature Map and CNN for Detection of People at the Beach," Journal of KIISE, JOK, vol. 46, no. 1, pp. 31-38, 2019. DOI: 10.5626/JOK.2019.46.1.31.


[ACM Style]

Gwiseong Moon and Yoon Kim. 2019. A Combined Model of Outline Feature Map and CNN for Detection of People at the Beach. Journal of KIISE, JOK, 46, 1, (2019), 31-38. DOI: 10.5626/JOK.2019.46.1.31.


[KCI Style]

문귀성, 김윤, "해안 물놀이객 검출을 위한 외곽선 특징맵과 CNN의 결합 모델," 한국정보과학회 논문지, 제46권, 제1호, 31~38쪽, 2019. DOI: 10.5626/JOK.2019.46.1.31.


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