18.3.4.1 Motion Segmentation, Motion Saliency, Video Salience

Chapter Contents (Back)
Motion Segmentation. Motion Saliency. 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

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

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


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

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

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

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
Spatio-Temporal Motion Segmentation, Flow Based Segmentation .


Last update:Dec 23, 2019 at 15:47:08