Automatic Arm Region Segmentation and Background Image Composition

Automatic Arm Region Segmentation and Background Image Composition

초록

In first-person perspective training system, the users needs realistic experience. For providing this experience, the system should offer the users virtual and real images at the same time. We propose an automatic a persons’s arm segmentation and image composition method. It consists of arm segmentation part and image composition part. Arm segmentation uses an arbitrary image as input and outputs arm segment or alpha matte. It enables end-to-end learning because we make use of FCN in this part. Image composition part conducts image combination between the result of arm segmentation and other image like road, building, etc. To train the network in arm segmentation, we used arm images through dividing the videos that we took ourselves for the training data.

키워드

Arm region; Arm segmentation; Background composition; FCN; 팔 영역; 팔 분할; 배경 합성; FCN
제목
Automatic Arm Region Segmentation and Background Image Composition
제목 (타언어)
Automatic Arm Region Segmentation and Background Image Composition
저자
김동현; 박세훈; 서영건
DOI
10.9728/dcs.2017.18.8.1509
발행일
2017
저널명
디지털콘텐츠학회논문지
권
18
호
8
페이지
1509 ~ 1516