18.3.4.2 Motion Segmentation, Motion Saliency, Video Salience

Chapter Contents (Back)
Motion Segmentation. Motion Saliency. Salient Object. Video Saliency.

Yi, Y.[Yang], Ding, J.[Jia], Lai, J.L.[Jie-Ling],
A novel video salient object extraction method based on visual attention,
SP:IC(28), No. 1, January 2013, pp. 45-54.
Elsevier DOI 1301
Video object segmentation; Salient object extraction; Visual attention model; Attention object growing BibRef

Li, Y., Sheng, B., Ma, L., Wu, W., Xie, Z.,
Temporally Coherent Video Saliency Using Regional Dynamic Contrast,
CirSysVideo(23), No. 12, 2013, pp. 2067-2076.
IEEE DOI 1312
Computational efficiency. Region-based visual dynamic contrast. BibRef

Han, J., He, S., Qian, X., Wang, D., Guo, L., Liu, T.,
An Object-Oriented Visual Saliency Detection Framework Based on Sparse Coding Representations,
CirSysVideo(23), No. 12, 2013, pp. 2009-2021.
IEEE DOI 1312
Computer vision BibRef

Li, W.T.[Wei-Te], Chang, H.S.[Haw-Shiuan], Lien, K.C.[Kuo-Chin], Chang, H.T.[Hui-Tang], Wang, Y.F.,
Exploring Visual and Motion Saliency for Automatic Video Object Extraction,
IP(22), No. 7, 2013, pp. 2600-2610.
IEEE DOI conditional random field; foreground object extraction; foreground-background region separation; visual saliency 1307
BibRef

Li, W.T.[Wei-Te], Chang, H.T.[Hui-Tang], Lyu, H.S.[Hermes Shing], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Automatic saliency inspired foreground object extraction from videos,
ICIP12(1089-1092).
IEEE DOI 1302
BibRef

Yang, J., Zhao, G., Yuan, J., Shen, X., Lin, Z., Price, B., Brandt, J.,
Discovering Primary Objects in Videos by Saliency Fusion and Iterative Appearance Estimation,
CirSysVideo(26), No. 6, June 2016, pp. 1070-1083.
IEEE DOI 1606
Estimation BibRef

Pang, Y., Ye, L., Li, X., Pan, J.,
Incremental Learning With Saliency Map for Moving Object Detection,
CirSysVideo(28), No. 3, March 2018, pp. 640-651.
IEEE DOI 1804
Gaussian processes, image motion analysis, image sequences, learning (artificial intelligence), minimisation, subspace analysis BibRef

Xu, B., Niu, Y.,
Accurate Object Segmentation for Video Sequences via Temporal-Spatial-Frequency Saliency Model,
IEEE_Int_Sys(33), No. 1, January 2018, pp. 18-28.
IEEE DOI 1805
Cameras, Frequency-domain analysis, Image color analysis, Image segmentation, Object segmentation, Video sequences, visualization BibRef

Le, T.N.[Trung-Nghia], Sugimoto, A.[Akihiro],
Video Salient Object Detection Using Spatiotemporal Deep Features,
IP(27), No. 10, October 2018, pp. 5002-5015.
IEEE DOI 1808
BibRef
Earlier:
Contrast Based Hierarchical Spatial-Temporal Saliency for Video,
PSIVT15(734-748).
Springer DOI 1602
feature extraction, image colour analysis, image representation, image segmentation, object detection, random processes, video object segmentation BibRef

Chen, C., Li, S., Qin, H., Pan, Z., Yang, G.,
Bilevel Feature Learning for Video Saliency Detection,
MultMed(20), No. 12, December 2018, pp. 3324-3336.
IEEE DOI 1812
feature extraction, learning (artificial intelligence), Markov processes, object detection, video signal processing, Video Saliency Detection BibRef

Peng, Q., Cheung, Y.,
Automatic Video Object Segmentation Based on Visual and Motion Saliency,
MultMed(21), No. 12, December 2019, pp. 3083-3094.
IEEE DOI 1912
Manifolds, Visualization, Object segmentation, Motion segmentation, Image segmentation, Autoregressive processes, Labeling, graph model BibRef

Wen, H.F.[Hong-Fa], Zhou, X.F.[Xiao-Fei], Sun, Y.[Yaoqi], Zhang, J.Y.[Ji-Yong], Yan, C.G.[Cheng-Gang],
Deep fusion based video saliency detection,
JVCIR(62), 2019, pp. 279-285.
Elsevier DOI 1908
Video saliency, Convolutional network, Feature integration, Boundary BibRef

Patil, P.W., Murala, S.,
MSFgNet: A Novel Compact End-to-End Deep Network for Moving Object Detection,
ITS(20), No. 11, November 2019, pp. 4066-4077.
IEEE DOI 1911
Videos, Object detection, Estimation, Feature extraction, Lighting, Image color analysis, Saliency detection, Background estimation, CNN BibRef

Patil, P.W., Thawakar, O., Dudhane, A., Murala, S.,
Motion Saliency Based Generative Adversarial Network for Underwater Moving Object Segmentation,
ICIP19(1565-1569)
IEEE DOI 1910
Underwater medium, motion saliency, Generative adversarial network, frame segmentation BibRef

Maczyta, L.[Léo], Bouthemy, P.[Patrick], Meur, O.L.[Olivier Le],
CNN-based temporal detection of motion saliency in videos,
PRL(128), 2019, pp. 298-305.
Elsevier DOI 1912
Motion saliency, Temporal detection, CNN-based classification, Dominant motion estimation, Video analysis BibRef

Xu, M., Liu, B., Fu, P., Li, J., Hu, Y.H.,
Video Saliency Detection via Graph Clustering With Motion Energy and Spatiotemporal Objectness,
MultMed(21), No. 11, November 2019, pp. 2790-2805.
IEEE DOI 1911
Spatiotemporal phenomena, Visualization, Dynamics, Proposals, Feature extraction, Fuses, Video saliency, graph clustering BibRef

Chen, C., Wang, G., Peng, C., Zhang, X., Qin, H.,
Improved Robust Video Saliency Detection Based on Long-Term Spatial-Temporal Information,
IP(29), No. 1, 2020, pp. 1090-1100.
IEEE DOI 1911
Saliency detection, Deep learning, Quality assessment, Trajectory, Computational modeling, Color, Training, Video saliency detection, long-term information revealing BibRef

Lai, Q., Wang, W., Sun, H., Shen, J.,
Video Saliency Prediction Using Spatiotemporal Residual Attentive Networks,
IP(29), No. 1, 2020, pp. 1113-1126.
IEEE DOI 1911
Visualization, Computational modeling, Spatiotemporal phenomena, Dynamics, Task analysis, Data models, Predictive models, video saliency BibRef

Fang, Y., Ding, G., Li, J., Fang, Z.,
Deep3DSaliency: Deep Stereoscopic Video Saliency Detection Model by 3D Convolutional Networks,
IP(28), No. 5, May 2019, pp. 2305-2318.
IEEE DOI 1903
convolutional neural nets, deconvolution, feature extraction, image sequences, object detection, optimisation, 3D convolutional neural networks BibRef

Fang, Y.M.[Yu-Ming], Zhang, X.Q.[Xiao-Qiang], Yuan, F.N.[Fei-Niu], Imamoglu, N.[Nevrez], Liu, H.[Haiwen],
Video saliency detection by gestalt theory,
PR(96), 2019, pp. 106987.
Elsevier DOI 1909
Visual attention, Video saliency detection, Gestalt theory, Uncertainty weighting, Spatiotemporal saliency BibRef

Wang, Q.[Qiong], Zhang, L.[Lu], Zou, W.B.[Wen-Bin], Kpalma, K.[Kidiyo],
Salient video object detection using a virtual border and guided filter,
PR(97), 2020, pp. 106998.
Elsevier DOI 1910
Video salient object detection, Distance transform, Guided filter, Global motion BibRef

Wu, Z., Su, L., Huang, Q.,
Learning Coupled Convolutional Networks Fusion for Video Saliency Prediction,
CirSysVideo(29), No. 10, October 2019, pp. 2960-2971.
IEEE DOI 1910
computer vision, convolutional neural nets, feature extraction, image motion analysis, inference mechanisms, fully convolutional network BibRef

Li, J., Fu, K., Zhao, S., Ge, S.,
Spatiotemporal Knowledge Distillation for Efficient Estimation of Aerial Video Saliency,
IP(29), No. 1, 2020, pp. 1902-1914.
IEEE DOI 1912
Computational modeling, Redundancy, Estimation, Visualization, Data models, Spatiotemporal phenomena, Drones, aerial video BibRef

Zhang, K.[Kao], Chen, Z.Z.[Zhen-Zhong],
Video Saliency Prediction Based on Spatial-Temporal Two-Stream Network,
CirSysVideo(29), No. 12, December 2019, pp. 3544-3557.
IEEE DOI 1912
Feature extraction, Predictive models, Streaming media, Visualization, Spatiotemporal phenomena, Computational modeling, deep learning BibRef

Kavak, Y.[Yasin], Erdem, E.[Erkut], Erdem, A.[Aykut],
Hedging static saliency models to predict dynamic saliency,
SP:IC(81), 2020, pp. 115694.
Elsevier DOI 1912
Dynamic saliency, Hedge algorithm, Decision theoretic online learning, Feature integration BibRef

Jiang, L.[Lai], Xu, M.[Mai], Zhang, S.[Shanyi], Sigal, L.[Leonid],
DeepCT: A novel deep complex-valued network with learnable transform for video saliency prediction,
PR(102), 2020, pp. 107234.
Elsevier DOI 2003
Saliency prediction, Complex-valued network, Learnable transform, Convolutional LSTM BibRef

Fang, Y.M.[Yu-Ming], Zhang, C.[Chi], Min, X.[Xiongkuo], Huang, H.[Hanqin], Yi, Y.[Yugen], Zhai, G.T.[Guang-Tao], Lin, C.W.[Chia-Wen],
DevsNet: Deep Video Saliency Network using Short-term and Long-term Cues,
PR(103), 2020, pp. 107294.
Elsevier DOI 2005
Video saliency detection, Spatiotemporal saliency, 3D convolution network (3D-ConvNet), Bidirectional convolutional long-short term memory network (B-ConvLSTM) BibRef

Li, Y., Li, S., Chen, C., Hao, A., Qin, H.,
Accurate and Robust Video Saliency Detection via Self-Paced Diffusion,
MultMed(22), No. 5, May 2020, pp. 1153-1167.
IEEE DOI 2005
Saliency detection, Proposals, Video sequences, Spatial coherence, Computational modeling, Optical imaging, Optical sensors, self-paced saliency diffusion BibRef

Zhou, F.[Feng], Shuai, H.[Hui], Liu, Q.S.[Qing-Shan], Guo, G.D.[Guo-Dong],
Flow driven attention network for video salient object detection,
IET-IPR(14), No. 6, 11 May 2020, pp. 997-1004.
DOI Link 2005
BibRef

Zhang, Q., Wang, X., Wang, S., Sun, Z., Kwong, S., Jiang, J.,
Learning to Explore Saliency for Stereoscopic Videos Via Component-Based Interaction,
IP(29), 2020, pp. 5722-5736.
IEEE DOI 2005
Videos, Visualization, Stereo image processing, Computational modeling, deep learning BibRef

Wang, Q.[Qiong], Zhang, L.[Lu], Li, Y.[Yan], Kpalma, K.[Kidiyo],
Overview of deep-learning based methods for salient object detection in videos,
PR(104), 2020, pp. 107340.
Elsevier DOI 2005
Deep-learning, Salient object detection, Video BibRef

Shokri, M.[Mohammad], Harati, A.[Ahad], Taba, K.[Kimya],
Salient object detection in video using deep non-local neural networks,
JVCIR(68), 2020, pp. 102769.
Elsevier DOI 2005
Video saliency detection, Deep learning, Non-local neural networks, Fully convolutional neural networks BibRef

Xu, M., Liu, B., Fu, P., Li, J., Hu, Y.H., Feng, S.,
Video Salient Object Detection via Robust Seeds Extraction and Multi-Graphs Manifold Propagation,
CirSysVideo(30), No. 7, July 2020, pp. 2191-2206.
IEEE DOI 2007
Spatiotemporal phenomena, Dynamics, Manifolds, Object detection, Reliability, Visualization, Feature extraction, Video saliency, multi-graphs saliency propagation BibRef


Nekrasov, V., Chen, H., Shen, C., Reid, I.D.,
Architecture Search of Dynamic Cells for Semantic Video Segmentation,
WACV20(1959-1968)
IEEE DOI 2006
Computer architecture, Semantics, Optical imaging, Decoding, Image segmentation, Optical propagation, Biomedical optical imaging BibRef

Yan, P., Li, G., Xie, Y., Li, Z., Wang, C., Chen, T., Lin, L.,
Semi-Supervised Video Salient Object Detection Using Pseudo-Labels,
ICCV19(7283-7292)
IEEE DOI 2004
convolutional neural nets, image colour analysis, image enhancement, image motion analysis, image sequences, Coherence BibRef

Le, T., Sugimoto, A.,
Semantic Instance Meets Salient Object: Study on Video Semantic Salient Instance Segmentation,
WACV19(1779-1788)
IEEE DOI 1904
image segmentation, image sequences, mobile robots, object detection, robot vision, video signal processing, Dogs BibRef

Fan, D.P.[Deng-Ping], Wang, W.[Wenguan], Cheng, M.M.[Ming-Ming], Shen, J.B.[Jian-Bing],
Shifting More Attention to Video Salient Object Detection,
CVPR19(8546-8556).
IEEE DOI 2002
BibRef

Song, H.M.[Hong-Mei], Wang, W.[Wenguan], Zhao, S.[Sanyuan], Shen, J.B.[Jian-Bing], Lam, K.M.[Kin-Man],
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection,
ECCV18(XI: 744-760).
Springer DOI 1810
BibRef

Hoo, W.L., Chan, C.S.,
Anisotropic Partial Differential Equation Based Video Saliency Detection,
ICIP18(2311-2315)
IEEE DOI 1809
Saliency detection, Image color analysis, Tensile stress, Feature extraction, Task analysis, Discrete cosine transforms, partial differential equation BibRef

Xiao, B.[Bo], Wang, B.[Bin],
Efficient HD video and image salient object detection with hierarchical boolean map approach,
ICIVC17(1-7)
IEEE DOI 1708
Acceleration, Algorithm design and analysis, Feature extraction, Floods, Image resolution, Object detection, Visualization, hierarchical boolean map, parallel processing, salient object detection, video consistency BibRef

Zhang, L.[Long], Liu, Y.J.[Yu-Jun], Han, S.D.[Shou-Dong],
Video segmentation based on strong target constrained video saliency,
ICIVC17(356-360)
IEEE DOI 1708
Adaptive optics, Image color analysis, Image segmentation, Optical imaging, Robustness, Target tracking, full-connected conditional random field, object proposal, super-pixel, video saliency, video, segmentation BibRef

Wei, L., Wang, F., Li, X., Wu, F., Xiao, J.,
Graph-theoretic spatiotemporal context modeling for video saliency detection,
ICIP17(4197-4201)
IEEE DOI 1803
Atomic layer deposition, Context modeling, Manifolds, Saliency detection, Spatiotemporal phenomena, Video saliency BibRef

Hu, Y.T.[Yuan-Ting], Huang, J.B.[Jia-Bin], Schwing, A.G.[Alexander G.],
VideoMatch: Matching Based Video Object Segmentation,
ECCV18(VIII: 56-73).
Springer DOI 1810
BibRef
And:
Unsupervised Video Object Segmentation Using Motion Saliency-Guided Spatio-Temporal Propagation,
ECCV18(I: 813-830).
Springer DOI 1810
BibRef

Chan, K.L.,
Saliency/non-saliency segregation in video sequences using perception-based local ternary pattern features,
MVA17(510-513)
DOI Link 1708
Adaptation models, Color, Computational modeling, History, Image color analysis, Mathematical model, Video sequences BibRef

Xue, K.[Kang], Wang, X.[Xiying], Ma, G.Y.[Geng-Yu], Wang, H.T.[Hai-Tao], Nam, D.[Dong_Kyung],
A video saliency detection method based on spatial and motion information,
ICIP15(412-416)
IEEE DOI 1512
Classification; Motion; Saliency; Video BibRef

Lee, T.[Teahyung], Hwangbo, M.[Myung], Alan, T.[Tanfer], Tickoo, O.[Omesh], Iyer, R.[Ravishankar],
Low-complexity HOG for efficient video saliency,
ICIP15(3749-3752)
IEEE DOI 1512
low-complexity HOG; video saliency BibRef

Hiratani, A., Nakashima, R., Matsumiya, K., Kuriki, I., Shioiri, S.,
Considerations of Self-Motion in Motion Saliency,
ACPR13(783-787)
IEEE DOI 1408
feature extraction BibRef

Agarwal, D., Soni, N., Namboodiri, A.M.,
Salient object detection in SfM point cloud,
NCVPRIPG13(1-4)
IEEE DOI 1408
image motion analysis BibRef

Gan, C.[Chuang], Qin, Z.C.[Zeng-Chang], Xu, J.[Jia], Wan, T.[Tao],
Salient object detection in image sequences via spatial-temporal cue,
VCIP13(1-6)
IEEE DOI 1402
feature extraction BibRef

Xia, Y.[Yang], Hu, R.M.[Rui-Min], Huang, Z.K.[Zhen-Kun], Su, Y.[Yin],
A novel method for generation of motion saliency,
ICIP10(4685-4688).
IEEE DOI 1009
BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Interactive Motion Segmentation .


Last update:Jul 10, 2020 at 16:03:35