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Ghost Vehicle and Shadow Removal Approach for Traffic Surveillance and Monitoring at Various Intersections Using Computer Vision

Mohammad Farukh Hashmi, Avinash G. Keskar, Ravula Sai Kiran Reddy, Ambati Uday Kaushik
2015 International Journal of Multimedia and Ubiquitous Engineering  
This paper proposes computer vision based real time vehicle detection, tracking and classification at urban intersections.  ...  As traffic surveillance technology continues to grow worldwide vehicle detection, counting, tracking and classification are gaining importance.  ...  Special thanks to Director VNIT Nagpur for providing institutional facilities and needed administrative and authoritative support during the work at VNIT.  ... 
doi:10.14257/ijmue.2015.10.3.34 fatcat:7muaaatvrne5bm2t6w6hhc7mhm

A Multitask Cascading CNN with MultiScale Infrared Optical Flow Feature Fusion-Based Abnormal Crowd Behavior Monitoring UAV

Yanhua Shao, Wenfeng Li, Hongyu Chu, Zhiyuan Chang, Xiaoqiang Zhang, Huayi Zhan
2020 Sensors  
Due to their advantages of high mobility and easy deployment, unmanned aerial vehicles (UAV) have become a flexible monitoring platform in recent years.  ...  Finally, considering two typical abnormal crowd behaviors of crowd aggregating and crowd escaping, the experimental results show that the monitoring UAV system can detect abnormal crowd behaviors in public  ...  Then the crowd walks around at random. The average movement speed of the crowd tends to be stable, so the system does not alarm.  ... 
doi:10.3390/s20195550 pmid:32998316 pmcid:PMC7582990 fatcat:rml7dpe4l5bffbrv4b7ixmk5lm

Multi-perspective Video Analysis of Persons and Vehicles for Enhanced Situational Awareness [chapter]

Sangho Park, Mohan M. Trivedi
2006 Lecture Notes in Computer Science  
Our framework can be applied to broad range of situational awareness for emergency response, disaster prevention, human interactions in structured environments, and crowd movement analysis in wide-view  ...  Crowd density is estimated from the footage in homography plane. Experimental data show promising results.  ...  In wide-view open area, counting individuals may not be possible or robust especially when the site is crowded.  ... 
doi:10.1007/11760146_39 fatcat:55mlpmi4gfhn3ji37mhptq2tqa

Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms

J. Candamo, M. Shreve, D.B. Goldgof, D.B. Sapper, R. Kasturi
2010 IEEE transactions on intelligent transportation systems (Print)  
., vehicle vandalism), and person-facility/ location interactions (e.g., object left behind and trespassing).  ...  For example, loitering, people (crowd) counting, crowd flow (behavior) analysis, and person talking on a cell phone. 2) Multiple-person interactions (see Fig. 3 standing, waiting at checkpoint, evading  ...  Hence, using multiple cameras may further complicate crowd counting.  ... 
doi:10.1109/tits.2009.2030963 fatcat:tiajxro6sbc23p2rdaam2pwyna

The 4th AI City Challenge [article]

Milind Naphade, Shuo Wang, David Anastasiu, Zheng Tang, Ming-Ching Chang, Xiaodong Yang, Liang Zheng, Anuj Sharma, Rama Chellappa, Pranamesh Chakraborty
2020 arXiv   pre-print
Track 1 addressed video-based automatic vehicle counting, where the evaluation is conducted on both algorithmic effectiveness and computational efficiency.  ...  Track 3 addressed city-scale multi-target multi-camera vehicle tracking. Track 4 addressed traffic anomaly detection.  ...  To determine movement-specific vehicle counting, teams used both ROI-based and data-driven based MOI classifica-tion.  ... 
arXiv:2004.14619v1 fatcat:en54aiitirf4pd2g5djv255kli

A Multilayer Motion Direction Based Model for Tracking Vehicles at Intersections

2020 International Journal of Engineering  
Congestion, occlusion and undetermined motion flows are the nominated challenging issues of vehicle tracking at intersections.  ...  In addition, normal traffic flow may change at intersections due to accidents.  ...  They used Kalman filter for predicting movements. Their proposed method could not track motionless vehicles and in crowded scenes. Nateghinia et al.  ... 
doi:10.5829/ije.2020.33.10a.12 fatcat:7t7x2tm2prhgrfxmu6twdzfbla

Deep Learning Based Surveillance System for Open Critical Areas

Francesco Turchini, Lorenzo Seidenari, Tiberio Uricchio, Alberto Del Bimbo
2018 Inventions  
We report quantitative results for object counting, detection, parking analysis, and anomaly detection.  ...  When we have an intersection, we also understand the direction in which the intersection occurs by looking at the orientations of the triplets.  ...  and wrong direction movement).  ... 
doi:10.3390/inventions3040069 fatcat:dzavulkvzfcktbyofqszmgkxfq

Traffic flow estimation with data from a video surveillance camera

Aleksandr Fedorov, Kseniia Nikolskaia, Sergey Ivanov, Vladimir Shepelev, Alexey Minbaleev
2019 Journal of Big Data  
Our system is capable of counting and analyzing vehicles movement direction with a maximum relative error that is lower than 10%.  ...  Methodology This paper aims to develop a system for traffic flow estimation, i.e. for counting and classifying vehicles by their movement directions.  ... 
doi:10.1186/s40537-019-0234-z fatcat:j6dhjvzbe5c5ffdv7f5krivb4u

A real-time system for vehicle detection with shadow removal and vehicle classification based on vehicle features at urban roads

Issan Atouf, Wahban Yahya Al Okaishi, Abdelmoghit Zaaran, Ibtissam Slimani, Mohamed Benrabh
2020 International Journal of Power Electronics and Drive Systems (IJPEDS)  
The counting results can be used to estimate the traffic density at intersections, and adjust the timing of traffic light for the next light cycle.  ...  The traffic flow in urban areas is more complicated than the traffic flow in highway, due to the slow movement of vehicles and crowded traffic flows in urban areas.  ...  The counting results can be used to estimate the traffic density at intersections, and adjust the timing of traffic light for the next light cycle.  ... 
doi:10.11591/ijpeds.v11.i4.pp2091-2098 fatcat:gxrwuqy2frgnzpxnq3auvguhse

Analysis of a Transportation System With Correlated Network Intersections: A Case Study for a Central Urban City With High Seasonal Fluctuation Trends

Omar Tayan, Yasser M. Alginahi, Muhammad Nomani Kabir, Abdullah M. Al Binali
2017 IEEE Access  
vehicle-pedestrian movement conflicts.  ...  The presented model analysis first examines the influences exerted by network-correlations at intersection-points, and second, presents case-study evacuation scenarios examined under varying circumstances  ...  ACKNOWLEDGEMENTS The authors would like to thank the Deanship of Student Affairs at Taibah University for supporting the students to conduct the data collection and the Custodian of the VOLUME 5, 2017  ... 
doi:10.1109/access.2017.2695159 fatcat:qh5mfnnnyrg3hhpoqhyek325je

Pedestrian Traffic Operations in Urban Networks

Yinan Zheng, Lily Elefteriadou, Thomas Chase, Bastian Schroeder, Virginia Sisiopiku
2016 Transportation Research Procedia  
However, it does not comprehensively address pedestrian operations and does not consider some recent important findings such as pedestrian-vehicle interactions at crosswalks, pedestrian signal compliance  ...  The following topics are discussed: pedestrian movement models, pedestrian crossing behavior, pedestrianvehicle interactions.  ...  Signalized Intersections Pedestrian crossing behavior and vehicle interactions at signalized intersections depend on the traffic control features and intersection signal plans.  ... 
doi:10.1016/j.trpro.2016.06.012 fatcat:lylv3dhg7ffkvmwtceexvgt6ky

Vehicle detection and tracking in relatively crowded conditions

Wenhao Lu, Shengjin Wang, Xioaqing Ding
2009 2009 IEEE International Conference on Systems, Man and Cybernetics  
Aiming at vehicle detection and tracking problems in video monitoring and controlling system, this paper mainly studies vehicle detection and tracking problems in conditions of high traffic density in  ...  Finally, we implement a real-time vehicle detection and tracking system with the upper methods. Experiments give good results in relative crowded Conditions.  ...  There's many algorithms are based on vehicle movements. But, all the algorithms mentioned above are not robust to clutter scenes because they don't get the characteristic feature of vehicles.  ... 
doi:10.1109/icsmc.2009.5346721 dblp:conf/smc/LuWD09 fatcat:fs7dgidnrjfatd4uwco75fjy6e

Paging Inspector Sands: The Costs of Public Information

Sacha Kapoor, Arvind Magesan
2014 American Economic Journal: Economic Policy  
Robust Standard Errors clustered at the intersection level. 2.  ...  Robust Standard Errors clustered at the intersection level. 2.  ... 
doi:10.1257/pol.6.1.92 fatcat:xr3jnftcrnb7veg53ypckucb2a

Traffic Control using Computer Vision

Sreejith P S, Parvathi Kishore P
2019 IJARCCE  
As we know that it is the era of speed, so that nobody wants to wait for a long time at any cost. Everybody prefers to low traffic density streets.  ...  Vehicle density is measured using predefined classifiers available in image processing.  ...  Number of cars in specific region will calculated by the difference of entering and leaving vehicles.  ... 
doi:10.17148/ijarcce.2019.8406 fatcat:cdj2nk3q5bfafioushyyscp6oa

Wireless Sensors Network Application: A Decentralized Approach for Traffic Control and Management [chapter]

Faisal Ahmed, Magdi S.
2012 Wireless Sensor Networks - Technology and Applications  
Acknowledgement This work is supported by the deanship of scientific research (DSR) at KFUPM through research group project No. RG-1105-1. References  ...  Phasing reduces conflicts between traffic movements at signalized intersections.  ...  As the number of lanes counted by a single detector increases, the accuracy of the count decreases as multiple vehicles can occupy the same detector at the same time. 5.  ... 
doi:10.5772/48212 fatcat:qvuxre32hna65bwxtwzc3dkyae
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