17.1.3.7.6 Carried Objects, Carrying Objects

Chapter Contents (Back)
Carried Objects. Public Safety. Gait.

Haritaoglu, I.[Ismail], Cutler, R.[Ross], Harwood, D.[David], Davis, L.S.[Larry S.],
Backpack: Detection of People Carrying Objects Using Silhouettes,
CVIU(81), No. 3, March 2001, pp. 385-397.
DOI Link 0001
BibRef
Earlier: ICCV99(102-107).
IEEE DOI
See also Robust Real-Time Periodic Motion Detection, Analysis, and Applications. BibRef

Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long], Wu, X.D.[Xin-Dong], Maybank, S.J.[Stephen J.],
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition,
PAMI(29), No. 10, October 2007, pp. 1700-1715.
IEEE DOI
PDF File. 0710
BibRef
Earlier: A1, A2, A4, A3:
Human Carrying Status in Visual Surveillance,
CVPR06(II: 1670-1677).
IEEE DOI
PDF File. 0606
Gabor gait representation. BibRef

Chuang, C.H., Hsieh, J.W., Tsai, L.W., Chen, S.Y., Fan, K.C.,
Carried Object Detection Using Ratio Histogram and its Application to Suspicious Event Analysis,
CirSysVideo(19), No. 6, June 2009, pp. 911-916.
IEEE DOI 0906
BibRef

Hsieh, J.W.[Jun-Wei], Cheng, J.C.[Jiun-Chen], Chen, L.C.[Li-Chih], Chuang, C.H.[Chi-Hung], Chen, D.Y.[Duan-Yu],
Handheld object detection and its related event analysis using ratio histogram and mixture of HMMs,
JVCIR(25), No. 6, 2014, pp. 1399-1415.
Elsevier DOI 1407
Behavior analysis BibRef

Qu, X., Nussbaum, M.A.,
Simulating Human Lifting Motions Using Fuzzy-Logic Control,
SMC-A(39), No. 1, January 2009, pp. 109-118.
IEEE DOI 0901
BibRef

Damen, D.[Dima], Hogg, D.C.[David C.],
Detecting Carried Objects from Sequences of Walking Pedestrians,
PAMI(34), No. 6, June 2012, pp. 1056-1067.
IEEE DOI 1205
BibRef
Earlier:
Detecting Carried Objects in Short Video Sequences,
ECCV08(III: 154-167).
Springer DOI 0810
BibRef
Earlier:
Associating People Dropping off and Picking up Objects,
BMVC07(xx-yy).
PDF File. 0709
Motion and shape, compare to templates of unencumbered pedestrians. Protrusions to get carried object, and compare to location.
See also Explaining Activities as Consistent Groups of Events: A Bayesian Framework Using Attribute Multiset Grammars. BibRef

Yang, L.[Le], Chen, G.[Gao], Li, G.[Gang],
Classification of Personnel Targets with Baggage Using Dual-band Radar,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
identify passengers with different baggage. BibRef

Al-Tayyan, A.[Amer], Assaleh, K.[Khaled], Shanableh, T.[Tamer],
Decision-level fusion for single-view gait recognition with various carrying and clothing conditions,
IVC(61), No. 1, 2017, pp. 54-69.
Elsevier DOI 1704
Biometrics BibRef

Ghadiri, F.[Farnoosh], Bergevin, R.[Robert], Bilodeau, G.A.[Guillaume-Alexandre],
From superpixel to human shape modelling for carried object detection,
PR(89), 2019, pp. 134-150.
Elsevier DOI 1902
BibRef
Earlier:
Carried Object Detection Based on an Ensemble of Contour Exemplars,
ECCV16(VII: 852-866).
Springer DOI 1611
Superpixel, Shape context, Codebook, Carried object BibRef

Debnath, R.[Rajib], Bhowmik, M.K.[Mrinal Kanti],
Novel framework for automatic localisation of gun carrying by moving person using various indoor and outdoor mimic and real-time views/Scenes,
IET-IPR(14), No. 17, 24 December 2020, pp. 4663-4675.
DOI Link 2104
BibRef

Li, X.[Xiang], Makihara, Y.S.[Yasu-Shi], Xu, C.[Chi], Yagi, Y.S.[Yasu-Shi], Ren, M.W.[Ming-Wu],
Gait recognition invariant to carried objects using alpha blending generative adversarial networks,
PR(105), 2020, pp. 107376.
Elsevier DOI 2006
BibRef
Earlier:
Gait Recognition via Semi-supervised Disentangled Representation Learning to Identity and Covariate Features,
CVPR20(13306-13316)
IEEE DOI 2008
Alpha blending, Generative adversarial network, Gait recognition, Carried objects. Clothing, Decoding, Training, Face recognition, Feature extraction, Image color analysis BibRef

Russel, N.S.[Newlin Shebiah], Selvaraj, A.[Arivazhagan],
Gender discrimination, age group classification and carried object recognition from gait energy image using fusion of parallel convolutional neural network,
IET-IPR(15), No. 1, 2021, pp. 239-251.
DOI Link 2106
BibRef

Li, L.[Li], Prabhu, S.[Saiesh], Xie, Z.Y.[Zi-Yang], Wang, H.[Hanwen], Lu, L.[Lu], Xu, X.[Xu],
Lifting Posture Prediction With Generative Models for Improving Occupational Safety,
HMS(51), No. 5, October 2021, pp. 494-503.
IEEE DOI 2109
Task analysis, Generators, Predictive models, Decoding, Prediction algorithms, Training, Generative adversarial networks, posture prediction BibRef

Wang, X.[Xuan], Hu, Y.H.[Yu Hen], Lu, M.L.[Ming-Lun], Radwin, R.G.[Robert G.],
Load Asymmetry Angle Estimation Using Multiple-View Videos,
HMS(51), No. 6, December 2021, pp. 734-739.
IEEE DOI 2112
Cameras, Pose estimation, Estimation error, Asymmetry angle, manual lifting, video monitoring BibRef


Piao, J., Inoshita, T., Iwamoto, K.,
Carried Object Recognition via Location Relation with Body Parts,
ICIP19(3058-3062)
IEEE DOI 1910
carried object recognition, human-object relation, attention map BibRef

Smailis, C., Vrigkas, M., Kakadiaris, I.A.,
Recaspia: Recognizing Carrying Actions in Single Images Using Privileged Information,
ICIP19(26-30)
IEEE DOI 1910
Action Recognition, Static Images, Privileged Information, LUPI, Deep Learning BibRef

Delgado, B., Tahboub, K., Delp, E.J.,
Superpixels shape analysis for carried object detection,
CVAST16(1-6)
IEEE DOI 1511
object detection BibRef

Lamar-León, J.[Javier], Baryolo, R.A.[Raul Alonso], García-Reyes, E.B.[Edel B.], Gonzalez-Diaz, R.[Rocío],
Gait-Based Carried Object Detection Using Persistent Homology,
CIARP14(836-843).
Springer DOI 1411
BibRef
Earlier: A1, A3, A4, Only:
Human Gait Identification Using Persistent Homology,
CIARP12(244-251).
Springer DOI 1209
BibRef

Dondera, R.[Radu], Morariu, V.I.[Vlad I.], Davis, L.S.[Larry S.],
Learning to Detect Carried Objects with Minimal Supervision,
SISM13(759-766)
IEEE DOI 1309
BibRef

Senst, T.[Tobias], Kuhn, A.[Alexander], Theisel, H.[Holger], Sikora, T.[Thomas],
Detecting People Carrying Objects Utilizing Lagrangian Dynamics,
AVSS12(398-403).
IEEE DOI 1211
BibRef

Senst, T.[Tobias], Evangelio, R.H.[Ruben Heras], Sikora, T.[Thomas],
Detecting people carrying objects based on an optical flow motion model,
WACV11(301-306).
IEEE DOI 1101

See also II-LK: A Real-Time Implementation for Sparse Optical Flow. BibRef

Singh, S.[Shamsher], Biswas, K.K.,
Biometric Gait Recognition with Carrying and Clothing Variants,
PReMI09(446-451).
Springer DOI 0912
BibRef

Ben-Abdelkader, C., Davis, L.S.,
Detection of people carrying objects: A Motion-Based Recognition Approach,
AFGR02(363-368).
IEEE DOI 0206
BibRef

Branca, A., Leo, M., Attolico, G., Distante, A.,
Detection of objects carried by people,
ICIP02(III: 317-320).
IEEE DOI 0210
BibRef

Spagnolo, P., Leo, M., Leone, A., Attolico, G., Distante, A.,
Posture estimation in visual surveillance of archaeological sites,
AVSBS03(277-283).
IEEE DOI 0310
BibRef

Spagnolo, P., Leo, M., Attolico, G., Distante, A.,
A Supervised Approach in Background Modelling for Visual Surveillance,
AVBPA03(592-599).
Springer DOI 0310
BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Unattended Package, Abandoned Luggage, Left Luggage, Theft .


Last update:Mar 16, 2024 at 20:36:19