18.3.4.4 Hough, Voting, Accumulation Methods for Moving Object Extraction

Chapter Contents (Back)
Object Segmentation. Sequence Analysis. Motion Segmentation. Hough Transform. Voting.

Fennema, C.L., and Thompson, W.B.,
Velocity Determination in Scenes Containing Several Moving Objects,
CGIP(9), No. 4, April 1979, pp. 301-315.
Elsevier DOI Hough. Motion, Segmentation. Similar to the Lucas technique, but earlier (and not referenced initially by Lucas ( See also Generalized Image Matching by the Method of Differences. )). Uses a hough technique for translation estimate and relaxation for motion based segmentation. See also Analysis of Accretion and Deletion at Boundaries in Dynamic Scenes. BibRef 7904

Fermin, I., Imiya, A., Ichikawa, A.,
Randomized Polygon Search for Planar Motion Detection,
PRL(17), No. 10, September 2 1996, pp. 1109-1115. Rigid Motion. Point Correspondences. Hough Transform. BibRef 9609

Imiya, A.[Atsushi], Fermin, I.[Iris],
Voting method for planarity and motion detection,
IVC(17), No. 12, October 1999, pp. 867-879.
Elsevier DOI See also Voting method for the detection of subpixel flow field. BibRef 9910

Sakai, T.[Tomoya], Imiya, A.[Atsushi],
Randomized algorithm of spectral clustering and image/video segmentation using a minority of pixels,
MLMotion09(468-475).
IEEE DOI 0910
BibRef

Ohnishi, N.[Naoya], Imiya, A.[Atsushi], Sakai, T.[Tomoya],
Unification of Multichannel Motion Feature Using Boolean Polynomial,
ISVC09(II: 807-816).
Springer DOI 0911
BibRef

Kšlvišinen, H.[Heikki],
Motion Detection Using the Randomized Hough Transform: Exploiting Gradient Information and Detecting Multiple Moving-Objects,
VISP(143), No. 6, December 1996, pp. 361-369. 9702
BibRef
Earlier:
Motion estimation and the Randomized Hough Transform (RHT): New methods with gradient information,
CAIP93(191-198).
Springer DOI 9309
BibRef

Kalviainen, H., Oja, E., Xu, L.,
Randomized Hough Transform Applied to Translational and Rotational Motion Analysis,
ICPR92(I:672-675).
IEEE DOI Hough, Motion. BibRef 9200

Nash, J.M., Carter, J.N., Nixon, M.S.,
Dynamic Feature-Extraction via the Velocity Hough Transform,
PRL(18), No. 10, October 1997, pp. 1035-1047. 9802
BibRef
Earlier:
The Velocity Hough Transform: A New Technique for Dynamic Feature Extraction,
ICIP97(II: 386-389).
IEEE DOI BibRef

Lappas, P.[Pelopidas], Carter, J.N.[John N.], Damper, R.I.[Robert I.],
Robust evidence-based object tracking,
PRL(23), No. 1-3, January 2002, pp. 253-260.
Elsevier DOI 0201
BibRef
Earlier:
Object Tracking Via the Dynamic Velocity Hough Transform,
ICIP01(II: 371-374).
IEEE DOI 0108
BibRef

Wixson, L.E.,
Detecting Salient Motion by Accumulating Directionally-Consistent Flow,
PAMI(22), No. 8, August 2000, pp. 774-780.
IEEE DOI 0010
BibRef
Earlier: Add A2: Hansen, M.W.[Mike W.], ICCV99(797-804).
IEEE DOI Motion detection, but only the interesting motions. Use cumulative consistent flow. BibRef

Wildes, R.P., Wixson, L.E.,
Detecting Salient Motion Using Spatiotemporal Filters and Optical Flow,
DARPA98(349-356). BibRef 9800

Wixson, L.E.[Lambert Ernest], Hsu, S.C.[Stephen Charles],
Method and apparatus for detecting object movement within an image sequence,
US_Patent5,847,755, 12/08/1998.
HTML Version. BibRef 9812

Wixson, L.E.[Lambert Ernest],
Method and apparatus for image-based object detection and tracking,
US_Patent6,434,254, Aug 13, 2002
WWW Link. BibRef 0208

Hill, L., Vlachos, T.,
Optimal search in Hough parameter hyperspace for estimation of complex motion in image sequences,
VISP(149), No. 2, April 2002, pp. 63-71.
IEEE Top Reference. 0208
BibRef

Piroddi, R., Vlachos, T.,
A Simple Framework for Spatio-Temporal Video Segmentation and Delayering Using Dense Motion Fields,
SPLetters(13), No. 7, July 2006, pp. 421-424.
IEEE DOI 0606
BibRef
Earlier:
Multiple-Feature Spatiotemporal Segmentation of Moving Sequences using a Rule-based Approach,
BMVC02(Poster Session). 0208
BibRef

Argyriou, V.,
Sub-Hexagonal Phase Correlation for Motion Estimation,
IP(20), No. 1, January 2011, pp. 110-120.
IEEE DOI 1101
BibRef

Argyriou, V., Vlachos, T.,
Quad-Tree Motion Estimation in the Frequency Domain Using Gradient Correlation,
MultMed(9), No. 6, October 2007, pp. 1147-1154.
IEEE DOI 0905
See also Subpixel Registration With Gradient Correlation. BibRef

Ren, J., Jiang, J., Vlachos, T.,
High-Accuracy Sub-Pixel Motion Estimation From Noisy Images in Fourier Domain,
IP(19), No. 5, May 2010, pp. 1379-1384.
IEEE DOI 1004
BibRef

Argyriou, V.[Vasileios], Vlachos, T.,
Performance study of gradient correlation for sub-pixel motion estimation in the frequency domain,
VISP(152), No. 1, February 2005, pp. 107-114.
IEEE Abstract. 0501
BibRef
And:
A study of sub-pixel motion estimation using phase correlation,
BMVC06(I:387).
PDF File. 0609
BibRef
Earlier:
Motion Estimation Using Quad-Tree Phase Correlation,
ICIP05(I: 1081-1084).
IEEE DOI 0512
BibRef

Argyriou, V.[Vasileios], Tzimiropoulos, G.[Georgios],
Frequency domain subpixel registration using HOG phase correlation,
CVIU(155), No. 1, 2017, pp. 70-82.
Elsevier DOI 1702
Phase correlation BibRef

Min, C.K.[Chang-Ki], Medioni, G.[Gťrard],
Inferring Segmented Dense Motion Layers Using 5D Tensor Voting,
PAMI(30), No. 9, September 2008, pp. 1589-1602.
IEEE DOI
PDF File. 0808
BibRef
Earlier:
Motion Segmentation by Spatiotemporal Smoothness Using 5D Tensor Voting,
PercOrg06(199).
IEEE DOI
PDF File. 0609
BibRef
Earlier:
Matching and Interpretation of Planar Motion Using Tensor Voting,
PercOrg04(57).
IEEE DOI 0502
See also Tensor Voting Accelerated by Graphics Processing Units (GPU). BibRef

Dinh, T.B.[Thang B.], Medioni, G.[Gerard],
Two-Frames Accurate Motion Segmentation Using Tensor Voting and Graph-Cuts,
Motion08(1-8).
IEEE DOI
PDF File. 0801
BibRef

Liu, C.[Chang], Yuen, P.C.[Pong C.], Qiu, G.P.[Guo-Ping],
Object motion detection using information theoretic spatio-temporal saliency,
PR(42), No. 11, November 2009, pp. 2897-2906.
Elsevier DOI 0907
Moving object detection; Foreground detection BibRef

Kim, W., Jung, C., Kim, C.,
Spatiotemporal Saliency Detection and Its Applications in Static and Dynamic Scenes,
CirSysVideo(21), No. 4, April 2011, pp. 446-456.
IEEE DOI 1104
BibRef

Kim, W.J.[Won-Jun], Kim, C.[Changick],
Spatiotemporal Saliency Detection Using Textural Contrast and Its Applications,
CirSysVideo(24), No. 4, April 2014, pp. 646-659.
IEEE DOI 1405
computer vision BibRef

Jung, C., Kim, C.,
A Unified Spectral-Domain Approach for Saliency Detection and Its Application to Automatic Object Segmentation,
IP(21), No. 3, March 2012, pp. 1272-1283.
IEEE DOI 1203
BibRef

Liu, Y.Y.[Ying-Ying], Wang, Y.[Yang], Sowmya, A.[Arcot], Chen, F.[Fang],
Soft Hough Forest-ERTs: Generalized Hough Transform based object detection from soft-labelled training data,
PR(60), No. 1, 2016, pp. 145-156.
Elsevier DOI 1609
Object detection BibRef

Xu, J.[Jie], Wang, Y.[Yang], Wang, W.[Wei], Yang, J.[Jun], Li, Z.D.[Zhi-Dong],
Unsupervised Moving Object Detection with On-line Generalized Hough Transform,
ACCV10(III: 145-156).
Springer DOI 1011
See also Spatial-Temporal Affinity Propagation for Feature Clustering with Application to Traffic Video Analysis. BibRef


Fagadar-Cosma, M.[Mihai], Cretu, V.I.[Vladimir-Ioan], Micea, M.V.[Mihai Victor],
Dense and Sparse Optic Flows Aggregation for Accurate Motion Segmentation in Monocular Video Sequences,
ICIAR12(I: 208-215).
Springer DOI 1206
BibRef

Kulkarni, M., Rajagopalan, A.N.,
Tensor Voting Based Foreground Object Extraction,
NCVPRIPG11(86-89).
IEEE DOI 1205
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

Shafik, M.S.E.N.[M. Salah E.N.], Mertsching, B.[Baerbel],
Fast Saliency-Based Motion Segmentation Algorithm for an Active Vision System,
ACIVS08(xx-yy).
Springer DOI 0810
BibRef

Tian, Y.L.[Ying-Li], Hampapur, A.[Arun],
Robust Salient Motion Detection with Complex Background for Real-Time Video Surveillance,
Motion05(II: 30-35).
IEEE DOI 0502
BibRef

Hung, H., Gong, S.,
Quantifying Temporal Saliency,
BMVC04(xx-yy).
HTML Version. 0508
BibRef

Vernon, D.,
Segmentation in Dynamic Image Sequences by Isolation of Coherent Wave Profiles,
ECCV96(I:293-303).
Springer DOI Find the velocity in Hough space, separate the object in Fourier space. BibRef 9600

Chapter on Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Moving Object Extraction Using Edges .


Last update:Apr 26, 2017 at 10:20:07