Bottesch, H.W.[H. Werner],
Freas, D.A.[David A.],
Passive vehicle presence detection system,
US_Patent5,166,681, 07/30/1990.
HTML Version. Simple detector of something there.
BibRef
9007
Pang, C.C.C.,
Lam, W.W.L.,
Yung, N.H.C.,
A Method for Vehicle Count in the Presence of Multiple-Vehicle
Occlusions in Traffic Images,
ITS(8), No. 3, September 2007, pp. 441-459.
IEEE DOI
0710
BibRef
Unzueta, L.,
Nieto, M.,
Cortes, A.,
Barandiaran, J.,
Otaegui, O.,
Sanchez, P.,
Adaptive Multicue Background Subtraction for Robust Vehicle Counting
and Classification,
ITS(13), No. 2, June 2012, pp. 527-540.
IEEE DOI
1206
BibRef
Somasundaram, G.,
Sivalingam, R.,
Morellas, V.,
Papanikolopoulos, N.,
Classification and Counting of Composite Objects in Traffic Scenes
Using Global and Local Image Analysis,
ITS(14), No. 1, March 2013, pp. 69-81.
IEEE DOI
1303
BibRef
Zhao, R.,
Wang, X.,
Counting Vehicles from Semantic Regions,
ITS(14), No. 2, 2013, pp. 1016-1022.
IEEE DOI Clustering algorithms; Semantics; Tracking;
Semantic region; vehicle counting
1307
BibRef
Taghvaeeyan, S.,
Rajamani, R.,
Portable Roadside Sensors for Vehicle Counting, Classification, and
Speed Measurement,
ITS(15), No. 1, February 2014, pp. 73-83.
IEEE DOI
1403
Global Positioning System
BibRef
Wang, R.[Rui],
Zhang, L.[Lei],
Xiao, K.J.[Ke-Jiang],
Sun, R.L.[Rong-Li],
Cui, L.[Li],
EasiSee: Real-Time Vehicle Classification and Counting via Low-Cost
Collaborative Sensing,
ITS(15), No. 1, February 2014, pp. 414-424.
IEEE DOI
1403
cameras
BibRef
Moranduzzo, T.,
Melgani, F.,
Automatic Car Counting Method for Unmanned Aerial Vehicle Images,
GeoRS(52), No. 3, March 2014, pp. 1635-1647.
IEEE DOI
1403
automobiles
BibRef
Liang, M.[Mingpei],
Huang, X.Y.[Xin-Yu],
Chen, C.H.[Chung-Hao],
Chen, X.[Xin],
Tokuta, A.[Alade],
Counting and Classification of Highway Vehicles by Regression
Analysis,
ITS(16), No. 5, October 2015, pp. 2878-2888.
IEEE DOI
1511
image classification
BibRef
Salvadori, C.[Claudio],
Petracca, M.[Matteo],
Bocchino, S.[Stefano],
Pelliccia, R.[Riccardo],
Pagano, P.[Paolo],
A low-cost vehicle counter for next-generation ITS,
RealTimeIP(10), No. 4, December 2015, pp. 741-757.
Springer DOI
1512
BibRef
Kamkar, S.,
Safabakhsh, R.,
Vehicle detection, counting and classification in various conditions,
IET-ITS(10), No. 6, 2016, pp. 406-413.
DOI Link
1608
feature extraction
BibRef
Irhebhude, M.E.[Martins E.],
Nawahda, A.[Amin],
Edirisinghe, E.A.[Eran A.],
View Invariant Vehicle Type Recognition and Counting System using
Multiple Features,
IJCVSP(6), No. 1, 2016, pp. 3.
PDF File.
1612
BibRef
Zhang, Y.S.[Yun-Sheng],
Zhao, C.[Chihang],
Zhang, Q.[Qiuge],
Counting vehicles in urban traffic scenes using foreground time-spatial
images,
IET-ITS(11), No. 2, March 2017, pp. 61-67.
DOI Link
1703
BibRef
Xu, H.X.[Hai-Xia],
Zhou, W.[Wei],
Zhu, J.[Jiang],
Huang, X.[Xia],
Wang, W.[Wei],
Vehicle counting based on double virtual lines,
SIViP(11), No. 5, July 2017, pp. 905-912.
WWW Link.
1706
BibRef
Yang, H.H.[Hong-Hong],
Qu, S.[Shiru],
Real-time vehicle detection and counting in complex traffic scenes
using background subtraction model with low-rank decomposition,
IET-ITS(12), No. 1, February 2018, pp. 75-85.
DOI Link
1801
BibRef
Balid, W.,
Tafish, H.,
Refai, H.H.,
Intelligent Vehicle Counting and Classification Sensor for Real-Time
Traffic Surveillance,
ITS(19), No. 6, June 2018, pp. 1784-1794.
IEEE DOI
1806
Algorithm design and analysis, Estimation, Magnetometers,
Real-time systems, Reliability, Surveillance, Vehicle detection,
vehicles detection and classification
BibRef
Gao, Z.,
Zhai, R.,
Wang, P.,
Yan, X.,
Qin, H.,
Tang, Y.,
Ramesh, B.,
Synergizing Appearance and Motion With Low Rank Representation for
Vehicle Counting and Traffic Flow Analysis,
ITS(19), No. 8, August 2018, pp. 2675-2685.
IEEE DOI
1808
Spatiotemporal phenomena, Vehicle detection, Robustness, Lighting,
Cameras, Matrix decomposition, Training, Appearance and motion,
traffic flow
BibRef
Chen, L.[Lili],
Zhang, Z.[Zhengdao],
Peng, L.[Li],
Fast single shot multibox detector and its application on vehicle
counting system,
IET-ITS(12), No. 10, December 2018, pp. 1406-1413.
DOI Link
1812
BibRef
Wang, Z.L.[Zi-Lei],
Liu, X.[Xu],
Feng, J.S.[Jia-Shi],
Yang, J.[Jian],
Xi, H.S.[Hong-Sheng],
Compressed-Domain Highway Vehicle Counting by Spatial and Temporal
Regression,
CirSysVideo(29), No. 1, January 2019, pp. 263-274.
IEEE DOI
1901
BibRef
Earlier: A2, A1, A3, A5, Only:
Highway Vehicle Counting in Compressed Domain,
CVPR16(3016-3024)
IEEE DOI
1612
Videos, Feature extraction, Road transportation, Estimation,
Surveillance, Metadata, Algorithm design and analysis,
compressed domain
BibRef
Jiang, T.[Tao],
Cai, M.D.[Ming-Dai],
Zhang, Y.L.[Yu-Long],
Jia, X.J.[Xiao-Jie],
Fast video-based queue length detection approach for self-organising
traffic control,
IET-ITS(13), No. 4, April 2019, pp. 670-676.
DOI Link
1903
BibRef
Czyzewski, A.[Andrzej],
Kotus, J.[Józef],
Szwoch, G.[Grzegorz],
Estimating Traffic Intensity Employing Passive Acoustic Radar and
Enhanced Microwave Doppler Radar Sensor,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Li, S.[Shuang],
Chang, F.L.[Fa-Liang],
Liu, C.S.[Chun-Sheng],
Li, N.J.[Nan-Jun],
Vehicle counting and traffic flow parameter estimation for dense
traffic scenes,
IET-ITS(14), No. 12, December 2020, pp. 1517-1523.
DOI Link
2011
BibRef
Li, S.[Shuang],
Chang, F.[Faliang],
Liu, C.S.[Chun-Sheng],
Bi-Directional Dense Traffic Counting Based on Spatio-Temporal
Counting Feature and Counting-LSTM Network,
ITS(22), No. 12, December 2021, pp. 7395-7407.
IEEE DOI
2112
Feature extraction, Bidirectional control, Estimation,
Vehicle detection, Solid modeling, Real-time systems,
counting Long Short-Term Memory (cLSTM)
BibRef
Liu, C.H.[Cheng-Huan],
Huynh, D.Q.[Du Q.],
Sun, Y.C.[Yu-Chao],
Reynolds, M.[Mark],
Atkinson, S.[Steve],
A Vision-Based Pipeline for Vehicle Counting, Speed Estimation, and
Classification,
ITS(22), No. 12, December 2021, pp. 7547-7560.
IEEE DOI
2112
Cameras, Pipelines, Detectors, Videos, Australia, Urban areas,
Intelligent transportation systems (ITS),
camera calibration
BibRef
Liu, L.[Liang],
Cao, Z.G.[Zhi-Guo],
Lu, H.[Hao],
Xiong, H.P.[Hai-Peng],
Shen, C.H.[Chun-Hua],
NSSNet: Scale-Aware Object Counting With Non-Scale Suppression,
ITS(23), No. 4, April 2022, pp. 3103-3114.
IEEE DOI
2204
Feature extraction, Transportation, Estimation, Fuses, Monitoring,
Task analysis, Object counting, intelligent transportation,
multi-scale models
BibRef
Yu, X.Y.[Xiao-Yuan],
Liang, Y.Y.[Yan-Yan],
Lin, X.X.[Xu-Xin],
Wan, J.[Jun],
Wang, T.[Tian],
Dai, H.N.[Hong-Ning],
Frequency Feature Pyramid Network With Global-Local Consistency Loss
for Crowd-and-Vehicle Counting in Congested Scenes,
ITS(23), No. 7, July 2022, pp. 9654-9664.
IEEE DOI
2207
Feature extraction, Data mining, Convolution, Task analysis,
Frequency-domain analysis, Correlation, Kernel, Context prediction,
global-local consistency loss
BibRef
Xu, H.H.[Hong-Hui],
Cai, Z.P.[Zhi-Peng],
Li, R.[Ruinian],
Li, W.[Wei],
Efficient CityCam-to-Edge Cooperative Learning for Vehicle Counting
in ITS,
ITS(23), No. 9, September 2022, pp. 16600-16611.
IEEE DOI
2209
Urban areas, Cameras, Videos, Feature extraction, Kernel, Servers,
Magnetic sensors, CityCam-to-Edge, vehicle counting,
lightweight scheme
BibRef
Meng, Y.[Yanda],
Bridge, J.[Joshua],
Zhao, Y.T.[Yi-Tian],
Joddrell, M.[Martha],
Qiao, Y.H.[Yi-Hong],
Yang, X.Y.[Xiao-Yun],
Huang, X.W.[Xiao-Wei],
Zheng, Y.L.[Ya-Lin],
Transportation Object Counting With Graph-Based Adaptive Auxiliary
Learning,
ITS(24), No. 3, March 2023, pp. 3422-3437.
IEEE DOI
2303
Task analysis, Adaptation models, Representation learning,
Feature extraction, Cognition, Transportation, Training,
adaptive auxiliary task
BibRef
Liao, L.[Liang],
Xiao, J.[Jing],
Yang, Y.[Yan],
Ma, X.[Xujie],
Wang, Z.[Zheng],
Satoh, S.[Shin'ichi],
High temporal frequency vehicle counting from low-resolution
satellite images,
PandRS(198), 2023, pp. 45-59.
Elsevier DOI
2304
Vehicle counting, Satellite images,
Temporal frequency observation, Spatial consistency, Location consistency
BibRef
Cao, Q.X.[Qian-Xia],
Shan, Z.Y.[Zhen-Yu],
Long, K.[Kejun],
Wang, Z.W.[Zheng-Wu],
GhostCount: A lightweight convolution network based on high-altitude
video for vehicle instantaneous counting in dense traffic scenes,
IET-ITS(17), No. 5, 2023, pp. 943-959.
DOI Link
2305
convolutional neural nets, edge detection,
intelligent transportation systems, road traffic
BibRef
Zhao, B.[Bin],
Han, P.F.[Peng-Fei],
Li, X.L.[Xue-Long],
Vehicle Perception From Satellite,
PAMI(46), No. 4, April 2024, pp. 2545-2554.
IEEE DOI
2403
Satellites, Videos, Task analysis, Object detection, Surveillance,
Traffic control, Deep learning, Density estimation, remote sensing,
vehicle counting
BibRef
Dobeš, P.[Petr],
Španhel, J.[Jakub],
Bartl, V.[Vojtech],
Juránek, R.[Roman],
Herout, A.[Adam],
Density-Based Vehicle Counting with Unsupervised Scale Selection,
DICTA20(1-8)
IEEE DOI
2201
Training, Annotations, Predictive models, Robustness, Task analysis,
Standards, Drones, Object counting, Traffic surveillance, Deep learning
BibRef
Ranjan, V.[Viresh],
Sharma, U.[Udbhav],
Nguyen, T.[Thu],
Hoai, M.[Minh],
Learning To Count Everything,
CVPR21(3393-3402)
IEEE DOI
2111
WWW Link.
Code, Counting. Visualization, Codes, Annotations, Animals, Detectors
BibRef
Ha, S.V.U.[Synh Viet-Uyen],
Chung, N.M.[Nhat Minh],
Nguyen, T.C.[Tien-Cuong],
Phan, H.N.[Hung Ngoc],
Tiny-PIRATE: A Tiny model with Parallelized Intelligence for
Real-time Analysis as a Traffic countEr,
AICity21(4114-4123)
IEEE DOI
2109
Road transportation, Tracking, Image edge detection,
Computational modeling, Urban areas, Detectors, Real-time systems
BibRef
Kocur, V.[Viktor],
Ftácnik, M.[Milan],
Multi-Class Multi-Movement Vehicle Counting Based on CenterTrack,
AICity21(4004-4010)
IEEE DOI
2109
Tracking, Urban areas, Neural networks,
Object detection, Computer architecture
BibRef
Rangnekar, A.[Aneesh],
Yao, Y.[Yi],
Hoffman, M.[Matthew],
Divakaran, A.[Ajay],
Fine-tuning for One-look Regression Vehicle Counting in Low-shot Aerial
Datasets,
WAAMI20(5-18).
Springer DOI
2103
BibRef
Huang, J.,
Ding, G.,
Guo, Y.,
Yang, D.,
Wang, S.,
Wang, T.,
Zhang, Y.,
Drone-Based Car Counting via Density Map Learning,
VCIP20(239-242)
IEEE DOI
2102
Gaussian processes,
learning (artificial intelligence), drone-based car counting,
drone-based image
BibRef
Bui, K.N.,
Yi, H.,
Cho, J.,
A Vehicle Counts by Class Framework using Distinguished Regions
Tracking at Multiple Intersections,
City20(2466-2474)
IEEE DOI
2008
Tracking, Object detection, Monitoring, Feature extraction,
Vehicle detection, Trajectory, Artificial intelligence
BibRef
Abdelhalim, A.,
Abbas, M.,
Towards Real-time Traffic Movement Count and Trajectory
Reconstruction Using Virtual Traffic Lanes,
City20(2527-2533)
IEEE DOI
2008
Trajectory, Cameras, Video sequences, Tracking,
Graphical user interfaces, Real-time systems, Artificial intelligence
BibRef
Lu, J.C.[Jin-Cheng],
Xia, M.[Meng],
Gao, X.[Xu],
Yang, X.P.[Xi-Peng],
Tao, T.R.[Tian-Ran],
Meng, H.[Hao],
Zhang, W.[Wei],
Tan, X.[Xiao],
Shi, Y.F.[Yi-Feng],
Li, G.B.[Guan-Bin],
Ding, E.[Errui],
Robust and Online Vehicle Counting at Crowded Intersections,
AICity21(3997-4003)
IEEE DOI
2109
Tracking, Detectors
BibRef
Liu, Z.J.[Zhong-Ji],
Zhang, W.[Wei],
Gao, X.[Xu],
Meng, H.[Hao],
Tan, X.[Xiao],
Zhu, X.X.[Xiao-Xing],
Xue, Z.[Zhan],
Ye, X.Q.[Xiao-Qing],
Zhang, H.W.[Hong-Wu],
Wen, S.L.[Shi-Lei],
Ding, E.[Errui],
Robust Movement-Specific Vehicle Counting at Crowded Intersections,
City20(2617-2625)
IEEE DOI
2008
Feature extraction, Trajectory, Object tracking, Object detection,
Kalman filters, Task analysis
BibRef
Darji, D.,
Vejarano, G.,
Counting Static Targets Using an Unmanned Aerial Vehicle On-the-Fly
and Autonomously,
CRV18(206-213)
IEEE DOI
1812
Cameras, Automobiles, Unmanned aerial vehicles, Trajectory, Roads,
Portable computers, Target tracking, unmanned aerial vehicle,
target counting
BibRef
Bouaich, S.,
Mahraz, M.A.,
Riffi, J.,
Tairi, H.,
Vehicle counting system in real-time,
ISCV18(1-4)
IEEE DOI
1807
image motion analysis, nearest neighbour methods,
object detection, road traffic, road vehicles,
virtual line
BibRef
Zhang, S.,
Wu, G.,
Costeira, J.P.,
Moura, J.M.F.,
FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting
in City Cameras,
ICCV17(3687-3696)
IEEE DOI
1802
convolution, image resolution,
learning (artificial intelligence), neural nets,
Visualization
BibRef
Hsieh, M.R.,
Lin, Y.L.,
Hsu, W.H.,
Drone-Based Object Counting by Spatially Regularized Regional
Proposal Network,
ICCV17(4165-4173)
IEEE DOI
1802
SLAM (robots), automobiles, autonomous aerial vehicles, cameras,
mobile robots, object detection, robot vision, LPNs,
Videos
BibRef
Zhu, J.L.[Jian-Liang],
Ai, Y.F.[Yun-Feng],
Tian, B.[Bin],
Real-time vehicle queue estimation of large-scale traffic scene,
ICIVC17(1160-1165)
IEEE DOI
1708
Algorithm design and analysis, Estimation, Head, Safety,
background learning, high-speed toll station, vehicle queue estimation
BibRef
Katsuki, T.[Takayuki],
Morimura, T.[Tetsuro],
Idé, T.[Tsuyoshi],
Unsupervised object counting without object recognition,
ICPR16(3627-3632)
IEEE DOI
1705
Cameras, Indexes, Object recognition,
Training, Training, data
BibRef
Lessard, A.,
Belisle, F.,
Bilodeau, G.A.[Guillaume-Alexandre],
Saunier, N.,
The Counting App, or How to Count Vehicles in 500 Hours of Video,
Traffic16(1592-1600)
IEEE DOI
1612
BibRef
Sakla, W.A.[Wesam A.],
Konjevod, G.[Goran],
Mundhenk, T.N.[T. Nathan],
Deep Multi-modal Vehicle Detection in Aerial ISR Imagery,
WACV17(916-923)
IEEE DOI
1609
Image color analysis, Object detection, Proposals,
Spatial resolution, Vehicle, detection
BibRef
Mundhenk, T.N.[T. Nathan],
Konjevod, G.[Goran],
Sakla, W.A.[Wesam A.],
Boakye, K.[Kofi],
A Large Contextual Dataset for Classification, Detection and Counting
of Cars with Deep Learning,
ECCV16(III: 785-800).
Springer DOI
1611
BibRef
Quesada, J.,
Rodriguez, P.[Paul],
Automatic Vehicle Counting Method Based on Principal Component
Pursuit Background Modeling,
ICIP16(3822-3826)
IEEE DOI
1610
Computer vision
BibRef
Tourani, A.,
Shahbahrami, A.,
Vehicle counting method based on digital image processing algorithms,
IPRIA15(1-6)
IEEE DOI
1603
Kalman filters
BibRef
Shirazi, M.S.[Mohammad Shokrolah],
Morris, B.[Brendan],
Vision-Based Vehicle Counting with High Accuracy for Highways with
Perspective View,
ISVC15(II: 809-818).
Springer DOI
1601
BibRef
Wang, W.[Wei],
Gee, T.[Tim],
Price, J.[Jeff],
Qi, H.R.[Hai-Rong],
Real Time Multi-vehicle Tracking and Counting at Intersections from a
Fisheye Camera,
WACV15(17-24)
IEEE DOI
1503
Cameras; Real-time systems; Space vehicles; Target tracking; Trajectory
BibRef
Miller, N.[Nicholas],
Thomas, M.A.[Mohan A.],
Eichel, J.A.[Justin A.],
Mishra, A.[Akshaya],
A Hidden Markov Model for Vehicle Detection and Counting,
CRV15(269-276)
IEEE DOI
1507
Detectors
BibRef
Oñoro-Rubio, D.[Daniel],
López-Sastre, R.J.[Roberto J.],
Towards Perspective-Free Object Counting with Deep Learning,
ECCV16(VII: 615-629).
Springer DOI
1611
BibRef
Guerrero-Gómez-Olmedo, R.[Ricardo],
Torre-Jiménez, B.[Beatriz],
López-Sastre, R.J.[Roberto J.],
Maldonado-Bascón, S.[Saturnino],
Oñoro-Rubio, D.[Daniel],
Extremely Overlapping Vehicle Counting,
IbPRIA15(423-431).
Springer DOI
1506
BibRef
Tamersoy, B.[Birgi],
Aggarwal, J.K.,
Counting Vehicles in Highway Surveillance Videos,
ICPR10(3631-3635).
IEEE DOI
1008
BibRef
Earlier:
Robust Vehicle Detection for Tracking in Highway Surveillance Videos
Using Unsupervised Learning,
AVSBS09(529-534).
IEEE DOI
0909
BibRef
Hinz, S.[Stefan],
Weihing, D.[Diana],
Suchandt, S.[Steffen],
Bamler, R.[Richard],
Detection and velocity estimation of moving vehicles in high-resolution
spaceborne synthetic aperture radar data,
OTCBVS08(1-6).
IEEE DOI
0806
BibRef
Meyer, F.[Franz],
Hinz, S.[Stefan],
Laika, A.[Andreas],
Suchandt, S.[Steffen],
Bamler, R.[Richard],
Performance Analysis of Spaceborne SAR Vehicle Detection and Velocity
Estimation,
PCV06(xx-yy).
PDF File.
0609
BibRef
Hinz, S.,
Detection and counting of cars in aerial images,
ICIP03(III: 997-1000).
IEEE DOI
0312
BibRef
Chiu, M.Y.[Ming-Yee],
Depommier, R.,
Spindler, T.,
An embedded real-time vision system for 24-hour indoor/outdoor
car-counting applications,
ICPR04(III: 338-341).
IEEE DOI
0409
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Vehicle Tracking, Vehicle Motion Analysis .