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Multiframe-Based Identification
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Francois, E.,
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Sequence d'Images,
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0804
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Earlier:
Branch-and-bound hypothesis selection for two-view multiple structure
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IEEE DOI
0806
BibRef
Earlier:
Automatic Video Object Shape Extraction and its Classification with
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ICIP05(III: 437-440).
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See also Multistage Branch-and-Bound Merging for Planar Surface Segmentation in Disparity Space.
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High quality moving foreground. Non-planar background.
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ICPR21(3201-3208)
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Training, Adaptation models, Estimation error, Object detection,
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Paul, J.[Johny],
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See also Global optimization of wavelet-domain hidden Markov tree for image segmentation.
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IEICE(E100-D), No. 1, January 2017, pp. 220-224.
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PR(48), No. 11, 2015, pp. 3477-3487.
Elsevier DOI
1506
Image sequence segmentation
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Chattopadhyay, C.[Chiranjoy],
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Prominent moving object segmentation from moving camera video shots
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SIViP(9), No. 8, November 2015, pp. 1927-1934.
WWW Link.
1511
BibRef
Earlier:
STAR:
A Content Based Video Retrieval system for moving camera video shots,
NCVPRIPG13(1-4)
IEEE DOI
1408
content-based retrieval
BibRef
Chattopadhyay, C.[Chiranjoy],
Das, S.[Sukhendu],
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1601
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Chattopadhyay, C.[Chiranjoy],
Das, S.[Sukhendu],
Supervised framework for automatic recognition and retrieval of
interaction: a framework for classification and retrieving videos
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IET-CV(10), No. 3, 2016, pp. 220-227.
DOI Link
1604
learning (artificial intelligence)
BibRef
Okade, M.[Manish],
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A novel moving object segmentation framework utilizing camera motion
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1603
Block motion vectors
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Hu, W.,
Yang, Y.,
Zhang, W.,
Xie, Y.,
Moving Object Detection Using Tensor-Based Low-Rank and Saliently
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1702
decomposition
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Rozantsev, A.[Artem],
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Detecting Flying Objects Using a Single Moving Camera,
PAMI(39), No. 5, May 2017, pp. 879-892.
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1704
BibRef
Earlier:
Flying objects detection from a single moving camera,
CVPR15(4128-4136)
IEEE DOI
1510
Aircraft
BibRef
Chen, T.,
Lu, S.,
Object-Level Motion Detection From Moving Cameras,
CirSysVideo(27), No. 11, November 2017, pp. 2333-2343.
IEEE DOI
1712
Adaptive optics, Cameras, Histograms, Motion detection,
Motion segmentation, Optical imaging, Semantics,
moving camera
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El Tantawy, A.[Agwad],
Shehata, M.S.[Mohamed S.],
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SIViP(12), No. 4, May 2018, pp. 641-649.
WWW Link.
1805
BibRef
Earlier:
A novel method for segmenting moving objects in aerial imagery using
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ICPR16(3898-3903)
IEEE DOI
1705
BibRef
Earlier:
UT-MARO: Unscented Transformation and Matrix Rank Optimization for
Moving Objects Detection in Aerial Imagery,
ISVC15(I: 275-284).
Springer DOI
1601
BibRef
And:
Moving object detection from moving platforms using Lagrange
multiplier,
ICIP15(2586-2590)
IEEE DOI
1512
PCA.
Cameras, Image segmentation, Matrix decomposition,
Object segmentation, Optimization, Robustness, Springs
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El Tantawy, A.[Agwad],
Shehata, M.S.[Mohamed S.],
An Accelerated Sequential PCP-Based Method for Ground-Moving Objects
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IP(28), No. 12, December 2019, pp. 5991-6006.
IEEE DOI
1909
Videos, Cameras, Kinematics, Computational modeling,
Object detection, Null space, Springs,
inexact Newton method
BibRef
El Tantawy, A.[Agwad],
Shehata, M.S.[Mohamed S.],
KRMARO: Aerial Detection of Small-Size Ground Moving Objects Using
Kinematic Regularization and Matrix Rank Optimization,
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1906
Feature extraction, Object detection, Kinematics, Cameras,
Newton method, Adaptive optics, Optical imaging,
inexact newton method
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Zhang, Y.G.[Yu-Gui],
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1809
Optical flow estimation, The moving camera,
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Motion object boundary
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Xie, X.C.[Xiu-Chuan],
Yang, T.[Tao],
Zhang, Y.N.[Yan-Ning],
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2202
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Chen, Y.H.[Yu-Huan],
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Video Salient Object Detection via Multiple Time-scale Analysis,
ICPR18(2184-2189)
IEEE DOI
1812
Optical imaging, Image color analysis, Saliency detection,
Adaptive optics, Object detection, Optical sensors, Optical variables measurement
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Heo, B.,
Yun, K.,
Choi, J.Y.,
Appearance and motion based deep learning architecture
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ICIP17(1827-1831)
IEEE DOI
1803
Cameras, Contamination, Dynamics, Machine learning, Object detection,
Robustness, Training, Moving object detection, deep learning, moving camera
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Bideau, P.[Pia],
Menon, R.R.[Rakesh R.],
Learned-Miller, E.G.[Erik G.],
MoA-Net: Self-supervised Motion Segmentation,
OpticalFlow18(VI:715-730).
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1905
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Bideau, P.[Pia],
Learned-Miller, E.G.[Erik G.],
It's Moving! A Probabilistic Model for Causal Motion Segmentation in
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ECCV16(VIII: 433-449).
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1611
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Chung, W.[Won_Taek],
Kim, Y.[Yong_Hyun],
Kim, Y.J.[Yong-Joong],
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A two-stage foreground propagation for moving object detection in a
non-stationary,
AVSS16(187-193)
IEEE DOI
1611
Adaptation models
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Lopez-Perez, J.J.[Jose J.],
Ayala-Ramirez, V.[Victor],
Hernandez-Belmonte, U.H.[Uriel H.],
Dynamic Object Detection and Representation for Mobile Robot
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MCPR16(84-93).
Springer DOI
1608
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Yun, K.[Kimin],
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Robust and Fast Moving Object Detection in a Non-Stationary Camera
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ICIP15(4897-4901)
IEEE DOI
1512
Foreground probability based sampling
See also Robust Moving Object Detection Against Fast Illumination Change.
BibRef
Yi, K.M.[Kwang Moo],
Yun, K.[Kimin],
Kim, S.W.[Soo Wan],
Chang, H.J.[Hyung Jin],
Choi, J.Y.[Jin Young],
Detection of Moving Objects with Non-stationary Cameras in 5.8ms:
Bringing Motion Detection to Your Mobile Device,
IWMV13(27-34)
IEEE DOI
1309
gaussian model, mobile phone, motion detection
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Battistone, F.[Francesco],
Petrosino, A.[Alfredo],
Sanniti di Baja, G.[Gabriella],
GRUNTS: Graph Representation for UNsupervised Temporal Segmentation,
CIAP15(I:225-235).
Springer DOI
1511
BibRef
Liang, X.F.[Xue-Feng],
Zhang, C.C.[Cui-Cui],
Matsuyama, T.[Takashi],
Inlier Estimation for Moving Camera Motion Segmentation,
ACCV14(IV: 352-367).
Springer DOI
1504
BibRef
Koutlemanis, P.,
Zabulis, X.,
Ntelidakis, A.,
Argyros, A.A.,
Foreground Detection with a Moving RGBD Camera,
ISVC13(I:216-227).
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1310
BibRef
Xiang, X.[Xiang],
An Attempt to Segment Foreground in Dynamic Scenes,
ISVC11(I: 124-134).
Springer DOI
1109
BibRef
Khosla, D.[Deepak],
Uhlenbrock, R.[Ryan],
Chen, Y.[Yang],
A Low-Power Neuromorphic System for Real-Time Visual Activity
Recognition,
ISVC18(106-115).
Springer DOI
1811
BibRef
Chen, Y.[Yang],
Khosla, D.[Deepak],
Huber, D.[David],
Kim, K.[Kyungnam],
Cheng, S.Y.[Shinko Y.],
A Neuromorphic Approach to Object Detection and Recognition in Airborne
Videos with Stabilization,
ISVC11(II: 126-135).
Springer DOI
1109
BibRef
Cheng, S.Y.[Shinko Y.],
Chen, Y.[Yang],
Khosla, D.[Deepak],
Kim, K.[Kyungnam],
Optimal Multiclass Classifier Threshold Estimation with Particle Swarm
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ISVC11(II: 536-544).
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1109
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Hori, M.[Maiya],
Takahashi, H.[Hideyuki],
Kanbara, M.[Masayuki],
Yokoya, N.[Naokazu],
Removal of Moving Objects and Inconsistencies in Color Tone for an
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CVMAR10(62-71).
Springer DOI
1109
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Kim, J.[Jiman],
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Kim, D.J.[Dai-Jin],
Moving object detection under free-moving camera,
ICIP10(4669-4672).
IEEE DOI
1009
BibRef
Uchiyama, H.[Hiroyuki],
Deguchi, D.[Daisuke],
Takahashi, T.[Tomokazu],
Ide, I.[Ichiro],
Murase, H.[Hiroshi],
Removal of Moving Objects from a Street-View Image by Fusing Multiple
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ICPR10(3456-3459).
IEEE DOI
1008
BibRef
Sun, S.W.[Shih-Wei],
Huang, F.[Fay],
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Data-Driven Foreground Object Detection from a Non-stationary Camera,
ICPR10(3053-3056).
IEEE DOI
1008
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Escudero-Vinolo, M.[Marcos],
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A robust framework for region based video object segmentation,
ICIP10(3461-3464).
IEEE DOI
1009
BibRef
Tiburzi, F.[Fabrizio],
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Bescos, J.[Jesus],
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A ground truth for motion-based video-object segmentation,
ICIP08(17-20).
IEEE DOI
0810
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Escudero, M.[Marcos],
Tiburzi, F.[Fabrizio],
Bescos, J.[Jesus],
MPEG video object segmentation under camera motion and multimodal
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ICIP08(2668-2671).
IEEE DOI
0810
BibRef
Micheloni, C.[Christian],
Foresti, G.L.[Gian Luca],
Alberti, E.,
A new feature clustering method for object detection with an active
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ICIP04(IV: 2587-2590).
IEEE DOI
0505
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Woelk, F.[Felix],
Koch, R.[Reinhard],
Fast Monocular Bayesian Detection of Independently Moving Objects by a
Moving Observer,
DAGM04(27-35).
Springer DOI
0505
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Dahyot, R.,
Charbonnier, P.,
Heitz, F.,
Unsupervised Statistical Detection of Changing Objects in
Camera-in-motion Video,
ICIP01(I: 638-641).
IEEE DOI
0108
BibRef
Frazier, J., and
Nevatia, R.,
Detecting Moving Objects from a Moving Platform,
DARPA90(348-355).
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9000
USC Computer VisionUsed the CLM (of Jain) and an estimate of the FOE to find
moving regions in the image.
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Background Detection, Background Model .