6.5.4 Hough Forests for Feature Extraction

Chapter Contents (Back)
Hough Forests. Hough.

Lehmann, A.[Alain], Leibe, B.[Bastian], Van Gool, L.J.[Luc J.],
Fast PRISM: Branch and Bound Hough Transform for Object Class Detection,
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. 1402
BibRef
Earlier:
Branch&Rank: Non-Linear Object Detection,
BMVC11(xx-yy).
HTML Version. 1110
Award, BMVC, Best Impact. BibRef

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).
Springer DOI 1210
BibRef

Schulter, S.[Samuel], Leistner, C.[Christian], Roth, P.M.[Peter M.], Bischof, H.[Horst],
Unsupervised Object Discovery and Segmentation in Videos,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Schulter, S.[Samuel], Roth, P.M.[Peter M.], Bischof, H.[Horst],
Ordinal Random Forests for Object Detection,
GCPR13(261-270).
Springer DOI 1311
BibRef

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 1301
BibRef

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 BibRef

Knopp, J.[Jan], Prasad, M.[Mukta], Van Gool, L.J.[Luc J.],
Orientation invariant 3D object classification using Hough transform based methods,
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
BibRef

Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Sparse Representation Based Projections,
BMVC11(xx-yy).
HTML Version. 1110
BibRef


Scalzo, M.[Maria], Velipasalar, S.[Senem],
Agglomerative clustering for feature point grouping,
ICIP14(4452-4456)
IEEE DOI 1502
Clustering algorithms BibRef

Scalzo, M.[Maria], Velipasalar, S.[Senem],
Autonomous multi-scale object detection with hough forests,
ICIP14(1643-1647)
IEEE DOI 1502
Computer vision BibRef

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
BibRef

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],
A Discriminative Voting Scheme for Object Detection using Hough Forests,
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 .


Last update:Sep 18, 2017 at 11:34:11