• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/
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Indoor Space Recognition using Super-pixel and DNN


Kisang Kim, Hyung-Il Choi, Journal of Internet Computing and Services, Vol. 19, No. 3, pp. 43-48, Jun. 2018
10.7472/jksii.2018.19.3.43, Full Text:
Keywords: Deep Learning, Super-pixel, Indoor-space recognition

Abstract

In this paper, we propose an indoor-space recognition using DNN and super-pixel. In order to recognize the indoor space from the image, segmentation process is required for dividing an image Super-pixel is performed algorithm which can be divided into appropriate sizes. In order to recognize each segment, features are extracted using a proposed method. Extracted features are learned using DNN, and each segment is recognized using the DNN model. Experimental results show the performance comparison between the proposed method and existing algorithms.


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Cite this article
[APA Style]
Kim, K. & Choi, H. (2018). Indoor Space Recognition using Super-pixel and DNN. Journal of Internet Computing and Services, 19(3), 43-48. DOI: 10.7472/jksii.2018.19.3.43.

[IEEE Style]
K. Kim and H. Choi, "Indoor Space Recognition using Super-pixel and DNN," Journal of Internet Computing and Services, vol. 19, no. 3, pp. 43-48, 2018. DOI: 10.7472/jksii.2018.19.3.43.

[ACM Style]
Kisang Kim and Hyung-Il Choi. 2018. Indoor Space Recognition using Super-pixel and DNN. Journal of Internet Computing and Services, 19, 3, (2018), 43-48. DOI: 10.7472/jksii.2018.19.3.43.