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[期刊论文]

An indoor object fast detection method based on visual attention mechanism of fusion depth information in rgb image

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author:

Lin, C. (Lin, C..) [1] | He, B. (He, B..) [2] | Dong, S. (Dong, S..) [3]

Indexed by:

Scopus PKU CSCD

Abstract:

The traditional visual attention mechanism is complex and rough-detection for visual saliency detection indoor red-green-blue (RGB) image. In order to overcome these defects, a new fast visual saliency object detection method based on fusion depth information on indoor RGB image is proposed. A certain scale image is obtained by sub-sampling and pyramid-quantization to reduce the spatial resolution of the images so as to decrease the computational complexity. The intensity, red-green and yellow-blue three-channel features visual attention mechanism significant detection model is proposed to acquire saliency map. The saliency growing strategy is proposed to acquire the precise saliency region in the saliency analysis. The fusion depth information is utilized to detect the objects in salient region. The feasibility and effectiveness of the algorithm is verified in indoor detection experiments. ©, 2014, Science Press. All right reserved.

Keyword:

Attention mechanism; Detection; Machine vision; Significant region

Community:

  • [ 1 ] [Lin, C.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, Fujian 350108, China
  • [ 2 ] [He, B.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, Fujian 350108, China
  • [ 3 ] [Dong, S.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, Fujian 350108, China

Reprint 's Address:

  • [Lin, C.]School of Mechanical Engineering and Automation, Fuzhou UniversityChina

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Source :

Chinese Journal of Lasers

ISSN: 0258-7025

Year: 2014

Issue: 11

Volume: 41

1 . 8 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 7

30 Days PV: 1

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