16.7.4.2.2 HoG, Gradients, Histogram of Gradients for Human Detection, People Detection, Pedestrians

Chapter Contents (Back)
Human Detection. HoG. Motion. See also Human Detection, People Detection, Pedestrians, Locating. See also Tracking People, Human Tracking, Pedestrian Tracking.

Pang, G.[Guan], Wang, G.[Guijin], Lin, X.G.[Xing-Gang],
Real-Time Human Detection Using Hierarchical HOG Matrices,
IEICE(E93-D), No. 3, March 2010, pp. 658-661.
WWW Link. 1003
BibRef

Cao, H.[Hui], Yamaguchi, K.[Koichiro], Ohta, M.[Mitsuhiko], Naito, T.[Takashi], Ninomiya, Y.[Yoshiki],
Feature Interaction Descriptor for Pedestrian Detection,
IEICE(E93-D), No. 9, September 2010, pp. 2656-2659.
WWW Link. 1003
BibRef
Earlier: A1, A2, A4, A5, Only:
Pedestrian Recognition Using Second-Order HOG Feature,
ACCV09(II: 628-634).
Springer DOI 0909
See also Road Image Segmentation and Recognition Using Hierarchical Bag-of-Textons Method. BibRef

Cao, H.[Hui], Naito, T.[Takashi], Ninomiya, Y.[Yoshiki],
Approximate RBF kernel SVM and its applications in pedestrian classification,
MLMotion08(xx-yy). 0810
BibRef

Hua, C.S.[Chun-Sheng], Makihara, Y.S.[Yasu-Shi], Yagi, Y.S.[Yasu-Shi],
Pedestrian Detection by Using a Spatio-Temporal Histogram of Oriented Gradients,
IEICE(E96-D), No. 6, June 2013, pp. 1376-1386.
WWW Link. 1306
BibRef

Satpathy, A.[Amit], Jiang, X.D.[Xu-Dong], Eng, H.L.[How-Lung],
Human Detection by Quadratic Classification on Subspace of Extended Histogram of Gradients,
IP(23), No. 1, January 2014, pp. 287-297.
IEEE DOI 1402
BibRef
Earlier:
Extended Histogram of Gradients with Asymmetric Principal Component and Discriminant Analyses for Human Detection,
CRV11(64-71).
IEEE DOI 1105
BibRef
Earlier:
Extended Histogram of Gradients feature for human detection,
ICIP10(3473-3476).
IEEE DOI 1009
gradient methods BibRef

Kim, S.[Soojin], Cho, K.[Kyeongsoon],
Efficient Pedestrian Detection Using Multi-Scale HOG Features with Low Computational Complexity,
IEICE(E97-D), No. 2, February 2013, pp. 366-369.
WWW Link. 1402
BibRef

Marin, J., Vázquez, D.[David], López, A.M.[Antonio M.], Amores, J.[Jaume], Kuncheva, L.I.,
Occlusion Handling via Random Subspace Classifiers for Human Detection,
Cyber(44), No. 3, March 2014, pp. 342-354.
IEEE DOI 1404
image classification BibRef

González, A., Vázquez, D.[David], López, A.M.[Antonio M.], Amores, J.[Jaume],
On-Board Object Detection: Multicue, Multimodal, and Multiview Random Forest of Local Experts,
Cyber(47), No. 11, November 2017, pp. 3980-3990.
IEEE DOI 1710
Cameras, Detectors, Feature extraction, Laser radar, Object detection, Radio frequency, Multicue, multimodal, multiview (MV), object, detection BibRef

Marin, J.[Javier], Vazquez, D.[David], Lopez, A.M.[Antonio M.], Amores, J.[Jaume], Leibe, B.[Bastian],
Random Forests of Local Experts for Pedestrian Detection,
ICCV13(2592-2599)
IEEE DOI 1403
HOG; LBP; Local Experts; Pedestrian detection; Random Forest BibRef

Chen, P., Huang, C., Lien, C., Tsai, Y.,
An Efficient Hardware Implementation of HOG Feature Extraction for Human Detection,
ITS(15), No. 2, April 2014, pp. 656-662.
IEEE DOI 1404
Approximation methods BibRef

Whytock, T.P.[Tenika P.], Belyaev, A.[Alexander], Robertson, N.M.[Neil M.],
Dynamic Distance-Based Shape Features for Gait Recognition,
JMIV(50), No. 3, November 2014, pp. 314-326.
Springer DOI 1410
BibRef
Earlier:
Towards Robust Gait Recognition,
ISVC13(II:523-531).
Springer DOI 1311
BibRef
And:
Improving Robustness and Precision in GEI + HOG Action Recognition,
ISVC13(I:119-128).
Springer DOI 1310
BibRef

Li, N.[Nijun], Cheng, X.[Xu], Zhang, S.F.[Suo-Fei], Wu, Z.Y.[Zhen-Yang],
Realistic human action recognition by Fast HOG3D and self-organization feature map,
MVA(25), No. 7, October 2014, pp. 1793-1812.
WWW Link. 1410
BibRef

Cheng, X.[Xu], Li, N.[Nijun], Zhou, T.[Tongchi], Zhou, L.[Lin], Wu, Z.Y.[Zhen-Yang],
Robust Superpixel Tracking with Weighted Multiple-Instance Learning,
IEICE(E98-D), No. 4, April 2015, pp. 980-984.
WWW Link. 1505
BibRef

Liu, Y.F.[Yi-Feng], Zeng, L.[Lin], Huang, Y.[Yan],
An efficient HOG-ALBP feature for pedestrian detection,
SIViP(8), No. S1, December 2014, pp. 125-134.
WWW Link. 1411
BibRef

Hua, C.S.[Chun-Sheng], Makihara, Y.S.[Yasu-Shi], Yagi, Y.S.[Yasu-Shi], Iwasaki, S.[Shun], Miyagawa, K.[Keisuke], Li, B.[Bo],
Onboard monocular pedestrian detection by combining spatio-temporal hog with structure from motion algorithm,
MVA(26), No. 2-3, April 2015, pp. 161-183.
Springer DOI 1504
BibRef

Wu, S.[Si], Laganière, R.[Robert], Payeur, P.[Pierre],
Improving pedestrian detection with selective gradient self-similarity feature,
PR(48), No. 8, 2015, pp. 2364-2376.
Elsevier DOI 1505
Pedestrian detection BibRef

Wu, S.[Si], Wang, S., Laganière, R.[Robert], Liu, C., Wong, H.S., Xu, Y.,
Exploiting Target Data to Learn Deep Convolutional Networks for Scene-Adapted Human Detection,
IP(27), No. 3, March 2018, pp. 1418-1432.
IEEE DOI 1801
Adaptation models, Data models, Detectors, Feature extraction, Labeling, Training, Human detection, convolutional network, self-paced learning BibRef

Kim, W.J.[Won-Jun], Han, J.J.[Jae-Joon],
Directional coherence-based spatiotemporal descriptor for object detection in static and dynamic scenes,
MVA(28), No. 1-2, February 2017, pp. 49-59.
Springer DOI 1702
Histogram of orientations BibRef

Liu, B.Z.[Bao-Zhen], Wu, H.[Hang], Su, W.H.[Wei-Hua], Sun, J.G.[Jing-Gong],
Sector-ring HOG for rotation-invariant human detection,
SP:IC(54), No. 1, 2017, pp. 1-10.
Elsevier DOI 1704
Rotation-invariant detection BibRef

Liu, B.Z.[Bao-Zhen], Wu, H.[Hang], Su, W.H.[Wei-Hua], Zhang, W.C.[Wen-Chang], Sun, J.G.[Jing-Gong],
Rotation-invariant object detection using Sector-ring HOG and boosted random ferns,
VC(34), No. 5, May 2018, pp. 707-719.
WWW Link. 1804
BibRef


Rauf, R., Shahid, A.R., Ziauddin, S., Safi, A.A.,
Pedestrian detection using HOG, LUV and optical flow as features with AdaBoost as classifier,
IPTA16(1-4)
IEEE DOI 1703
feature extraction BibRef

Errami, M.[Mounir], Rziza, M.[Mohammed],
An Efficient Pedestrian Detector Based on Saliency and HOG Features Modeling,
ISVC16(II: 101-107).
Springer DOI 1701
BibRef

Balasubramanian, P., Pathak, S., Mittal, A.,
Improving Gradient Histogram Based Descriptors for Pedestrian Detection in Datasets with Large Variations,
Robust16(1177-1186)
IEEE DOI 1612
BibRef

Yuan, X.[Xu], Cai-nian, L.[Li], Xiao-liang, X.[Xu], Mei, J.[Jiang], Jian-guo, Z.[Zhang],
A two-stage hog feature extraction processor embedded with SVM for pedestrian detection,
ICIP15(3452-3455)
IEEE DOI 1512
FPGA BibRef

Mahmoud, A.[Ali], El-Barkouky, A.[Ahmed], Graham, J.[James], Farag, A.[Aly],
Pedestrian detection using mixed partial derivative based histogram of oriented gradients,
ICIP14(2334-2337)
IEEE DOI 1502
Histogram of Oriented Gradients BibRef

Miramontes-Jaramillo, D.[Daniel], Kober, V.[Vitaly], Díaz-Ramírez, V.H.[Víctor Hugo],
Rotation Invariant Tracking Algorithm Based on Circular HOGs,
MCPR15(115-124).
Springer DOI 1506
BibRef
Earlier:
A Robust Tracking Algorithm Based on HOGs Descriptor,
CIARP14(54-61).
Springer DOI 1411
BibRef
Earlier:
CWMA: Circular Window Matching Algorithm,
CIARP13(I:439-446).
Springer DOI 1311
BibRef

Beltrán-Herrera, A., Vázquez-Santacruz, E., Gamboa-Zuñiga, M.,
Real-Time Classification of Lying Bodies by HOG Descriptors,
MCPR14(211-220).
Springer DOI 1407
BibRef

Arie, M.[Makoto], Shibata, M.[Masatoshi], Terabayashi, K.[Kenji], Moro, A.[Alessandro], Umeda, K.[Kazunori],
Fast human detection using template matching for gradient images and aSC descriptors based on subtraction stereo,
ICIP13(3118-3122)
IEEE DOI 1402
Human detection BibRef

Takahisa, K.[Kishino], Sun, Z.[Zhe], Micheletto, R.[Ruggero],
A Fast and Precise HOG-Adaboost Based Visual Support System Capable to Recognize Pedestrian and Estimate Their Distance,
ACVR13(20-29).
Springer DOI 1309
BibRef

Salas, Y.S.[Yainuvis Socarrás], Bermudez, D.V.[David Vázquez], López Peña, A.M.[Antonio M.], Gomez, D.G.[David Gerónimo], Gevers, T.[Theo],
Improving HOG with Image Segmentation: Application to Human Detection,
ACIVS12(178-189).
Springer DOI 1209
BibRef

Kittipanya-Ngam, P.[Panachit], Lung, E.H.[Eng How],
HOG-Based Descriptors on Rotation Invariant Human Detection,
VS10(143-152).
Springer DOI 1109
BibRef

Geismann, P.[Philip], Knoll, A.[Alois],
Speeding Up HOG and LBP Features for Pedestrian Detection by Multiresolution Techniques,
ISVC10(I: 243-252).
Springer DOI 1011
BibRef

Zeng, C.B.[Cheng-Bin], Ma, H.D.[Hua-Dong], Ming, A.[Anlong],
Fast human detection using mi-sVM and a cascade of HOG-LBP features,
ICIP10(3845-3848).
IEEE DOI 1009
BibRef

Dong, L.[Li], Yu, X.G.[Xin-Guo], Li, L.Y.[Li-Yuan], Hoe, J.K.E.[Jerry Kah Eng],
HOG based multi-stage object detection and pose recognition for service robot,
ICARCV10(2495-2500).
IEEE DOI 1109
BibRef

Wang, X.Y.[Xioa-Yu], Han, T.X.[Tony X.], Yan, S.C.[Shui-Cheng],
An HOG-LBP Human Detector with Partial Occlusion Handling,
ICCV09(32-39).
IEEE DOI 0909
BibRef

Lillywhite, K.[Kirt], Lee, D.J.[Dah-Jye], Zhang, D.[Dong],
Real-time human detection using histograms of oriented gradients on a GPU,
WACV09(1-6).
IEEE DOI 0912
See also feature construction method for general object recognition, A. BibRef

Chuang, C.H.[Cheng-Hsiung], Huang, S.S.[Shih-Shinh], Fu, L.C.[Li-Chen], Hsiao, P.Y.[Pei-Yung],
Monocular multi-human detection using Augmented Histograms of Oriented Gradients,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Watanabe, T.[Tomoki], Ito, S.[Satoshi],
Two Co-occurrence Histogram Features Using Gradient Orientations and Local Binary Patterns for Pedestrian Detection,
ACPR13(415-419)
IEEE DOI 1408
application specific integrated circuits BibRef

Watanabe, T.[Tomoki], Ito, S.[Satoshi], Yokoi, K.[Kentaro],
Co-occurrence Histograms of Oriented Gradients for Pedestrian Detection,
PSIVT09(37-47).
Springer DOI 0901
BibRef

Mu, Y.D.[Ya-Dong], Yan, S.C.[Shui-Cheng], Liu, Y.[Yi], Huang, T.[Thomas], Zhou, B.F.[Bing-Feng],
Discriminative local binary patterns for human detection in personal album,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Wang, C.C.R.[Chi-Chen Raxle], Lien, J.J.J.[Jenn-Jier James],
AdaBoost Learning for Human Detection Based on Histograms of Oriented Gradients,
ACCV07(I: 885-895).
Springer DOI 0711
BibRef

Zhu, Q.A.[Qi-Ang], Yeh, M.C.[Mei-Chen], Cheng, K.T.[Kwang-Ting], Avidan, S.[Shai],
Fast Human Detection Using a Cascade of Histograms of Oriented Gradients,
CVPR06(II: 1491-1498).
IEEE DOI 0606
BibRef

Dalal, N.[Navneet], Triggs, B.[Bill],
Histograms of Oriented Gradients for Human Detection,
CVPR05(I: 886-893).
IEEE DOI 0507
Award, Longuet-Higgins. BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Motion Based Human Detection, Spatio-Temporal Analysis, Pedestrians .


Last update:Nov 17, 2018 at 09:12:27