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학술대회 The Study on Large Scale Image Processing Architecture Based on Hadoop2.0 Clusters
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저자
오봉진, 박종열, 진성근
발행일
201509
출처
International Conference on Consumer Electronics (ICCE) 2015 : Berlin, pp.474-475
DOI
https://dx.doi.org/10.1109/ICCE-Berlin.2015.7391314
협약과제
15MS4500, (1세부) 실시간 대규모 영상 데이터 이해·예측을 위한 고성능 비주얼 디스커버리 플랫폼 개발, 박경
초록
This paper describes the DeepView platform which is a pilot system to classify large scaled images collected from a VMS server based on Hadoop 2.0 clusters. Multiple DeepView Classifier tasks analyze images simultaneously to detect objects in the images. Classifier task is implemented as a direct YARN task instead of MapReduce task to avoid intensive disk I/O and limited input format. Moreover, the small data access problem of Hadoop can be avoided because Application Master controls YARN tasks to access only local blocks of image files before image classification starts.
키워드
Bigdata platform, Hadoop 2.0, Large scale image processing, VMS, YARN
KSP 제안 키워드
Data Access, Disk I/O, Image classification, Image files, Image processing, Large scale image, Processing architecture, Small data, pilot system