计算机科学 ›› 2018, Vol. 45 ›› Issue (10): 261-266.doi: 10.11896／j.issn.1002-137X.2018.10.048
袁小艳1, 王安志2, 王明辉3
YUAN Xiao-yan1, WANG An-zhi2, WANG Ming-hui3
摘要： 由于视觉注意预测能够快速、准确地定位图像中的显著区域,因此将视觉注意中的频域信息融入显著性目标检测中,从而有效地在复杂场景中检测显著性目标。首先,采用改进的频域检测方法对图像进行视觉注意预测,将该频域信息融入Focusness特征中计算得到频域信息聚焦特征,并将此特征与颜色特征进行融合得到前景显著图。然后,对RBD背景进行优化,得到背景显著图。最后,对前景显著图、背景显著图进行融合。在ESSCD,DUT-OMON两个具有挑战性的数据集上进行了大量实验,并采用PR_Curve,F-Measure,MAE对结果进行了评估,结果表明,所提出的方法要优于6种对比方法(HFT,PQFT,HDCT,UFO,DSR和RBD),并且能够处理复杂场景的图像。
中图分类号:
| [1]SHANG W L,JIAN L H,YAN M C.Saliency Detection Based on Spatio-Frequency Information[C]∥IEEE International Conference on Communication Software and Networks.2016:642-646. [2]BI F K,CHEN H,SHI H,et al.Identifying and Tracking Speci- fic Building Areas in Airborne Remote Sensing Video with Complicated Scenes[J].Journal of Electronics,2016,44(6):1394-1399.(in Chinese) 毕福昆,陈禾,师皓,等.机载复杂遥感场景下特定建筑区检测跟踪算法[J].电子学报,2016,44(6):1394-1399. [3]GAO Z Y,TANG W F,HE L J.Moving object detection with moving camera based on motion saliency[J].Journal of Compu-ters Application,2016,36(6):1692-1698.(in Chinese) 高智勇,唐文峰,贺良杰.基于运动显著性的移动镜头下的运动目标检测[J].计算机应用,2016,36(6):1692-1698. [4]BORJI A,ITTI L.Scene classification with a sparse set of sa- lient regions[C]∥IEEE International Conference on Robotics & Automation.2011:1902-1908. [5]ZHOU J B,REN Y F,YAN Y Y.Unsupervised Image Segmentation Based on Saliency Detection[J].Computer Science,2015,42(8):52-56.(in Chinese) 周静波,任永峰,严云洋.基于视觉显著性的非监督图像分割[J].计算机科学,2015,42(8):52-56. [6]LI S Q,ZENG C,LIU S P,et al.Merging fixation for saliency detection in a multilayer graph[J].Neurocomputing,2017,230(C):173-183. [7]WANG Z S,LI B X.A two-stage approach to saliency detection in images[C]∥International Conference on Acoustics,Speech and Signal Processing.IEEE,2008:965-968. [8]HOU X,ZHANG L.Saliency detection:A spectral residual approach[C]∥Conference on Computer Vision And PatternRecognition.IEEE,2007:1-8. [9]MISHRA A,ALOIMONOS Y,FAH C L.Active segmentation with fixation[C]∥IEEE Proceedings of the 12th International Conference on Computer Vision.2009:468-475. [10]LI J,LEVINE M D,AN X J,et al.Visual Saliency Based on Scale-Space Analysis in the Frequency Domain[J].IEEE Tran-sactions on Pattern Analysis and Machine Intelligence,2013,35(4):996-1010. [11]JIANG P,LING H B,YU J Y,et al.Salient Region Detection by UFO:Uniqueness,Focusness and Objectness[C]∥Proceedings of IEEE International Conference on Computer Vision.2013:1976-1983. [12]GUO C L,MA Q,ZHANG L M.Spatio-temporal Saliency Detection Using Phase Spectrum of Quaternion Fourier Transform[C]∥Proceedings of IEEE Computer Vision and Pattern Recognition.Anchorage,AK,2008:1-8. [13]ZHU W J,LIANG S,WEI Y C,et al.Saliency Optimization from Robust Background Detection[C]∥Proceedings of IEEE Computer Vision and Pattern Recognition.2014:2814-2821. [14]WANG J P,LU H C,LI X H,et al.Saliency detection via background and foreground seed selection[J].Neurocomputing,2015,152(C):359-368. [15]SUN X L,ZHU Z S,LIU X L,et al.Frequency-spatial domain based salient region detection[J].Optik,2015,126(9-10):942-949. [16]LIU S W,HU J L.Visual saliency based on frequency domain analysis and spatial information[J].Multimed Tools & Applications,2016,75(23):1-13. [17]ITTI L,KOCH C,NIEBUR E.A Model of Saliency-Based Visual Attention for Rapid Scene Analysis[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1998,20(11):1254-1259. [18]ZHAO B,DELP E J.Visual Saliency Models Based on Spectrum Processing[C]∥Proceedings of IEEE Winter Conference on Applications of Computer Vision.Waikoloa,HI,2015:976-981. [19]KIM J,HAN D,TAI Y W,et al.Salient Region Detection via High-Dimensional Color Transform[C]∥IEEE Computer Vision and Pattern Recognition.2014:883-890. [20]JIANG H Z,WANG J D,YUAN Z J,et al.Automatic Salient Object Segmentation Based on Context and Shape[C]∥British Machine Vision Conference.2011:1-12. [21]MARTIN D R,FOWLKES C C,MALIK J.Learning to detect natural image boundaries using local brightness,color,and texture cues[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2004,26(5):530-549. [22]QIN Y,LU H,XU Y,et al.Saliency detection via Cellular Automata[C]∥Proceedings of IEEE Computer Vision and Pattern Recognition.IEEE,2015:110-119. [23]CHUAN Y,HE L Z,CHUAN H L,et al.Saliency Detection Via Graph-Based Manifold Ranking[C]∥IEEE Computer Vision and Pattern Recognition.2013:3166-3173. |
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