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IJCV(94), No. 2, September 2011, pp. 175-197.
WWW Link.
1101
BibRef
Earlier:
PrISM: Principled Implicit Shape Model,
BMVC09(xx-yy).
PDF File.
0909
Generalized Hough for object detection.
BibRef
Rematas, K.[Konstantinos],
Leibe, B.[Bastian],
Efficient object detection and segmentation with a cascaded Hough
Forest ISM,
RobPerc11(966-973).
IEEE DOI
1201
BibRef
Lehmann, A.D.[Alain D.],
Gehler, P.V.[Peter V.],
Van Gool, L.J.[Luc J.],
Branch&Rank for Efficient Object Detection,
IJCV(106), No. 3, February 2014, pp. 252-268.
WWW Link.
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Earlier:
Branch&Rank: Non-Linear Object Detection,
BMVC11(xx-yy).
HTML Version.
1110
Award, BMVC, Best Impact.
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Gall, J.[Juergen],
Yao, A.,
Razavi, N.,
Van Gool, L.J.,
Lempitsky, V.[Victor],
Hough Forests for Object Detection, Tracking, and Action Recognition,
PAMI(33), No. 11, November 2011, pp. 2188-2202.
IEEE DOI
1110
Hough forests: random forests adapted to perform a generalized Hough transform.
See also Variations of a Hough-Voting Action Recognition System.
BibRef
Gall, J.[Juergen],
Razavi, N.[Nima],
Van Gool, L.J.[Luc J.],
An Introduction to Random Forests for Multi-class Object Detection,
WTFCV11(243-263).
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1210
BibRef
Schulter, S.[Samuel],
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Bischof, H.[Horst],
Unsupervised Object Discovery and Segmentation in Videos,
BMVC13(xx-yy).
DOI Link
1402
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Schulter, S.[Samuel],
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Bischof, H.[Horst],
Ordinal Random Forests for Object Detection,
GCPR13(261-270).
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Wohlhart, P.[Paul],
Schulter, S.[Samuel],
Köstinger, M.[Martin],
Roth, P.M.[Peter M.],
Bischof, H.[Horst],
Discriminative Hough Forests for Object Detection,
BMVC12(40).
DOI Link
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Poier, G.[Georg],
Schulter, S.[Samuel],
Sternig, S.[Sabine],
Roth, P.M.[Peter M.],
Bischof, H.[Horst],
Hough Forests Revisited:
An Approach to Multiple Instance Tracking from Multiple Cameras,
GCPR14(499-510).
Springer DOI
1411
BibRef
Roth, P.M.[Peter M.],
Leistner, C.[Christian],
Berger, A.[Armin],
Bischof, H.[Horst],
Multiple instance learning from multiple cameras,
WCN10(17-24).
IEEE DOI
1006
use the geometry (3D) from the multiple cameras starting from a small number
of positive samples.
BibRef
Schulter, S.[Samuel],
Leistner, C.[Christian],
Roth, P.M.[Peter M.],
Bischof, H.[Horst],
Van Gool, L.J.[Luc J.],
On-line Hough Forests,
BMVC11(xx-yy).
HTML Version.
1110
See also Alternating Regression Forests for Object Detection and Pose Estimation.
See also Accurate Object Detection with Joint Classification-Regression Random Forests.
BibRef
Razavi, N.[Nima],
Gall, J.[Juergen],
Van Gool, L.J.[Luc J.],
Scalable multi-class object detection,
CVPR11(1505-1512).
IEEE DOI
1106
BibRef
Earlier:
Backprojection Revisited: Scalable Multi-view Object Detection and
Similarity Metrics for Detections,
ECCV10(I: 620-633).
Springer DOI
1009
From Hough to the image.
BibRef
Barinova, O.[Olga],
Lempitsky, V.[Victor],
Kholi, P.[Pushmeet],
On Detection of Multiple Object Instances Using Hough Transforms,
PAMI(34), No. 9, September 2012, pp. 1773-1784.
IEEE DOI
1208
BibRef
Earlier:
CVPR10(2233-2240).
IEEE DOI Video of talk:
WWW Link.
1006
Award paper.
BibRef
Gall, J.[Juergen],
Lempitsky, V.[Victor],
Class-specific Hough forests for object detection,
CVPR09(1022-1029).
IEEE DOI
0906
BibRef
Srikantha, A.[Abhilash],
Gall, J.[Juergen],
Hough-based object detection with grouped features,
ICIP14(1653-1657)
IEEE DOI
1502
Computer vision
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Knopp, J.[Jan],
Prasad, M.[Mukta],
Van Gool, L.J.[Luc J.],
Orientation invariant 3D object classification using Hough transform
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3DOR10(15-20).
DOI Link
1111
See also Scene Cut: Class-Specific Object Detection and Segmentation in 3D Scenes.
BibRef
Knopp, J.[Jan],
Prasad, M.[Mukta],
Willems, G.[Geert],
Timofte, R.[Radu],
Van Gool, L.J.[Luc J.],
Hough Transform and 3D SURF for Robust Three Dimensional Classification,
ECCV10(VI: 589-602).
Springer DOI
1009
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Timofte, R.[Radu],
Van Gool, L.J.[Luc J.],
Sparse Representation Based Projections,
BMVC11(xx-yy).
HTML Version.
1110
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Scalzo, M.[Maria],
Velipasalar, S.[Senem],
Autonomous multi-scale object detection with hough forests,
ICIP14(1643-1647)
IEEE DOI
1502
Computer vision
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Henderson, C.,
Izquierdo, E.,
Minimal Hough Forest training for pattern detection,
WSSIP15(69-72)
IEEE DOI
1603
image recognition
BibRef
Do, T.D.[Trung Dung],
Vu, L.[Ly],
Nguyen, V.H.[Van Huan],
Kim, H.[Hale],
Full weighting Hough Forests for object detection,
AVSS14(253-258)
IEEE DOI
1411
Boosting
BibRef
Murai, Y.[Yusuke],
Yamauchi, Y.[Yuji],
Yamashita, T.[Takayoshi],
Fujiyoshi, H.[Hironobu],
Weighted Hough Forest for object detection,
MVA15(122-125)
IEEE DOI
1507
Accuracy
BibRef
Yamauchi, Y.[Yuji],
Takaki, M.[Masanari],
Yamashita, T.[Takayoshi],
Fujiyoshi, H.[Hironobu],
Feature co-occurrence representation based on boosting for object
detection,
SISM10(31-38).
IEEE DOI
1006
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Mühling, M.[Markus],
Ewerth, R.[Ralph],
Shi, B.[Bing],
Freisleben, B.[Bernd],
Multi-class Object Detection with Hough Forests Using Local Histograms
of Visual Words,
CAIP11(I: 386-393).
Springer DOI
1109
BibRef
Kumar, V.B.G.[Vijay B.G.],
Patras, I.[Ioannis],
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BMVCWS10(xx-yy).
HTML Version.
1009
BibRef
Chapter on Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform continues in
Multi-Resolution and Parallel Hough Transform .