NDLI: Objectness ranking by uniform Bayesian model with multimodal and global cues

Content Provider	IET Digital Library
Author	Zhang, Jianhua Xie, Zhen Xiao, Junhao Chen, Shengyong Zhang, Jianwei
Abstract	Category-independent object detection and localisation plays an important role in many computer vision tasks. In this study, an efficient method is proposed for generic objectness ranking by fusing two dimension (2D) or 3D information. A novel Bayesian model is designed to integrate multimodal cues and global cues to estimate object location, scale and number. In the pure trichannel colour space, the authors employ global spatial information as new global cues. From the colour+depth (red, green and blue+D) aspect, the authors compute multimodal saliency and oversegments to find two new multimodal cues. Local and regional depth cues are also explored and combined with them together so that a reliable objectness ranking scheme can be implemented. The proposed method is evaluated on web-public common 2D and RGB+D datasets. In RGB+D cases, the experimental results show that the proposed method achieves an average 5% improvement over state-of-the-art methods. Furthermore, for achieving the similar recall rates, the authors’ method only needs 30% amounts of sampled windows with respect of other available methods.
Starting Page	736
Ending Page	745
Page Count	10
ISSN	17519632
Volume Number	10
e-ISSN	17519640
Issue Number	Issue 7, Oct (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/10/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2015.0276
Journal	IET Computer Vision
Publisher Date	2016-04-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bayes Method Category Independent Object Detection Computer Vision Computer Vision And Image Processing Technique Global Cues Global Spatial Information Image Colour Analysis Multimodal Cues Multimodal Saliency Object Detection Object Location Objectness Ranking Optical, Image And Video Signal Processing Statistics Trichannel Colour Space Uniform Bayesian Model
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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