Scientific articles describing applications that use/implement/expand
principles of ViBe
Last update: December 23, 2021
1. Noise cancelling for tracking in robotic arc welding
Xiao, R., Xu, Y., Hou, Z., Chen, C., and Chen, S. A feature extraction algorithm based
on improved snake model for multi-pass seam tracking in robotic arc welding. Journal
of Manufacturing Processes, 72:48–60, December 2021. URL http://dx.doi.org/10.
1016/j.jmapro.2021.10.005
2. Background removal of dance clips
Wang, J., Wang, Y., Weng, N., Chai, T., Li, A., Zhang, F., and Yu, S. Will you ever
become popular? learning to predict virality of dance clips. CoRR, abs/2111.03819,
November 2021. URL https://arxiv.org/abs/2111.03819
3. Detection of construction cranes under a transmission line
Li, X. and Lu, L. Construction crane detection under transmission line based on im-
proved Vibe algorithm. In Earth and Environmental Science, volume 692 of Jour-
nal of Physics: Conference Series, pages 1–10. IOP Publishing, 2021. URL http:
//dx.doi.org/10.1088/1755-1315/692/2/022007
4. Tarmac monitoring
Zheng, D., Yuan, G., Wang, Y., and Zhou, H. Improved VIBE shadow elimination
method with adaptive threshold in the environment of tarmac monitoring. In Inter-
national Conference on Image and Graphics (ICIG), volume 12890 of Lecture Notes in
Computer Science, pages 328–340. Springer, 2021. URL http://dx.doi.org/10.1007/
978-3-030-87361-5_27
5. Prior extraction of video tubes for online surveillance video synopsis
Yang, Y., Kim, H., Choi, H., Chae, s., and Kim, I.J. Scene adaptive online surveillance
video synopsis via dynamic tube rearrangement using octree. IEEE Transactions on
Image Processing, 30:8318–8331, September 2021. URL http://dx.doi.org/10.1109/
TIP.2021.3114986
6. Tracking of multiple pedestrians in video surveillance
Wang, Z., Li, M., Lu, Y., Bao, Y., Li, Z., and Zhao, J. Effective multiple pedestrian
tracking system in video surveillance with monocular stationary camera. Expert Systems
with Applications, 178:1–13, September 2021. URL http://dx.doi.org/10.1016/j.
eswa.2021.114992
7. Liquid leakage detection
Doagang, P., Weiwei, L., Erjiang, Q., and Jie, H. Liquid leakage detection of power
plant pipelines based on improved Vibe algorithm. In Power System and Green Energy
Conference (PSGEC), pages 640–644. Shanghai, China, August 2021. URL http://
dx.doi.org/10.1109/PSGEC51302.2021.9542130
8. Detection of moving objects in satellite images
Huang, P., Wang, F., Xiang, Y., and You, H. Moving target detection and tracking of
1
satellite videos based on v-csk algorithm. Journal of University of Chinese Academy of
Sciences, 38(3):392–401, September 2021. URL http://html.rhhz.net/ZGKXYDXXB/
1621232673097-2049612410.htm
9. Smoke detection
Wang, Y., Han, Q., Li, Y., and Li, Y. Video smoke detection based on multi-feature
fusion and modified random forest. Engineering Letters, 29(3):1115–1122, Septem-
ber 2021. URL http://www.engineeringletters.com/issues_v29/issue_3/index.
html
10. Vision-based posture classification for postural ergonomic risk assessment
Seo, J. and Lee, S. Automated postural ergonomic risk assessment using vision-based
posture classification. Automation in Construction, 128:1–12, August 2021. URL http:
//dx.doi.org/10.1016/j.autcon.2021.103725
11. Gait recognition
Srinivasan, L. Improved gait recognition accuracy based on DFT-GEI. Research Square
preprint, August 2021. URL http://dx.doi.org/10.21203/rs.3.rs-655061/v2
12. Crowd emotion evaluation
Zhang, X., Yang, X., Zhang, W., Li, G., and Yu, H. Crowd emotion evaluation based on
fuzzy inference of arousal and valence. Neurocomputing, 445:194–205, July 2021. URL
http://dx.doi.org/10.1016/j.neucom.2021.02.047
13. Smoke detection from from forest fires
Gao, Y. and Cheng, P. Full-scale video-based detection of smoke from forest fires
combining ViBe and MSER algorithms. Fire Technology, 57:1637–1666, July 2021.
URL http://dx.doi.org/10.1007/s10694-020-01052-3
14. Abnormal behavior detection
Qiao, X., Zhu, W., Guo, D., Jiang, T., Chang, X., Zhou, Y., Zhu, D., and Cao, N.
Design of abnormal behavior detection system in the state grid business office. In
Advances in Artificial Intelligence and Security, volume 1423 of Communications in
Computer and Information Science, pages 510–520. Springer, June 2021. URL http:
//dx.doi.org/10.1007/978-3-030-78618-2_42
15. Posture recognition
Liu, Y. and Wu, Y. A multi-feature motion posture recognition model based on genetic
algorithm. Traitement du signal, 38(3):599–605, June 2021. URL http://dx.doi.org/
10.18280/ts.380307
16. Monitoring of power substation
Xu, L., Song, Y., Zhang, W., An, Y., Wang, Y., and Ning, H. An efficient foreign objects
detection network for power substation. Image and Vision Computing, 109:1–12, May
2021. URL http://dx.doi.org/10.1016/j.imavis.2021.104159
17. Detection of crowd abnormal behavior
Meng, B. and Li, D. Detection method for crowd abnormal behavior based on long short-
term memory network. In Advances in Intelligent Information Hiding and Multimedia
Signal Processing, volume 211 of Smart Innovation, Systems and Technologies, pages
305–313. Springer, 2021. URL http://dx.doi.org/10.1007/978-981-33-6420-2_38
2
18. Automatic visual inspection
Chen, W., Cai, N., Wang, H., Lin, J., and Wang, H. Automatic optical inspection
system for IC solder joint based on local-to-global ensemble learning. Soldering &
Surface Mount Technology, 33(2), March 2021. URL http://dx.doi.org/10.1108/
SSMT-03-2020-0011
19. Detection of low-altitude aerial targets
Sun, H., Liu, Q., Wang, J., Fen, J., Wu, Y., Zhao, H., and Li, H. Fusion of infrared
and visible images for remote detection of low-altitude slow-speed small targets. IEEE
Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14:2971–
2983, February 2021. URL http://dx.doi.org/10.1109/JSTARS.2021.3061496
20. Registration of videos captured by a UAV
Lemaire, P., Crispim-Junior, C., Robinault, L., and Tougne, L. Registering unmanned
aerial vehicle videos in the long term. Sensors, 21(2):1–19, January 2021. URL http:
//dx.doi.org/https://doi.org/10.3390/s21020513
21. Human counting and tracking using a ToF camera
Wang, H., Luo, H., Zhou, W., and Xie, D. A novel approach of human tracking and
counting using overhead ToF camera. In International Conference on Life System
Modeling and Simulation, volume 1303 of Communications in Computer and Infor-
mation Science, pages 416–429. Springer, 2021. URL http://dx.doi.org/10.1007/
978-981-33-6378-6_31
22. Detection of tampering in surveillance video footages
Vijayaraghavan, P., Nelson, M., Kandan, S., Prasanna, R., and Raghavendran, M.
Surveillance footage video tampering detection. Informatica: Journal of Applied Ma-
chines Electrical Electronics Computer Science and Communication Systems, 1(1):10–
17, December 2020. URL http://dx.doi.org/10.47812/IJAMECS2010102
23. Detection of small targets
Uzair, M., Brinkworth, R., and Finn, A. Bio-inspired video enhancement for small mov-
ing target detection. IEEE Transactions on Image Processing, 30:1232–1244, December
2020. URL http://dx.doi.org/10.1109/TIP.2020.3043113
24. Motion detection in a time-lapse camera for ecological studies
Winterl, A., Richter, S., Houstin, A., Neterova, A., Bonadonna, F., Schneider, W., Fabry,
B., Le Bohec, C., and Zitterbart, D. micrObs a customizable time-lapse camera for
ecological studies. HardwareX, 8:1–15, October 2020. URL http://dx.doi.org/10.
1016/j.ohx.2020.e00134
25. Smoke vehicle detection
Tao, H. and Liu, X. Smoke vehicle detection based on spatiotemporal Bag-Of-Features
and professional convolutional neural network. IEEE Transactions on Circuits and
Systems for Video Technology, 30(10):3301–3316, October 2020. URL http://dx.doi.
org/10.1109/TCSVT.2019.2920657
26. Detection of vacant spaces in parking lots
Varghese, A. and Sreelekha, G. An efficient algorithm for detection of vacant spaces
3
in delimited and non-delimited parking lots. IEEE Transactions on Intelligent Trans-
portation Systems, 21(10):4052–4062, October 2020. URL http://dx.doi.org/10.
1109/TITS.2019.2934574
27. Vehicle detection
Wang, X., Hu, X., Chen, C., Fan, Z., and Peng, S. Illuminating vehicles with motion
priors for surveillance vehicle detection. In IEEE International Conference on Image
Processing (ICIP), pages 2021–2025. Abu Dhabi, United Arab Emirates, October 2020.
URL http://dx.doi.org/10.1109/ICIP40778.2020.9190727
28. Fall detection
Kottari, K., Delibasis, K., and Maglogiannis, I. Real-time fall detection using un-
calibrated fisheye cameras. IEEE Transactions on Cognitive and Developmental Sys-
tems, 12(3):588–600, September 2020. URL http://dx.doi.org/10.1109/TCDS.2019.
2948786
29. Automatic fall detection
Wang, K., Cao, G., Meng, D., Chen, W., and Cao, W. Automatic fall detection of human
in video using combination of features. ProgrammerSought Web site, September 2020.
URL https://www.programmersought.com/article/93563604802/
30. Multiple object tracking
Siingh, K., Karar, V., and Poddar, S. Radius nearest neighbour based feature classi-
fication for occlusion handling. Pattern Recognition and Image Analysis, 30:416–427,
September 2020. URL http://dx.doi.org/10.1134/S1054661820030268
31. Blind background extraction from videos in the cloud for privacy protection
Jin, X., Yu, H., Zhang, H., Li, X., and Sun, H. Blind background extraction from videos
in the cloud. Multimedia Tools and Applications, 79:28755–28771, August 2020. URL
http://dx.doi.org/10.1007/s11042-020-09386-4
32. Smoke detection
Yin, Y., Cheng, H., and Liu, H. Flue gas layer feature segmentation based on multi-
channel pixel adaptive. Multimedia Tools and Applications, 79:29069–29085, August
2020. URL http://dx.doi.org/10.1007/s11042-020-09466-5
33. Maritime moving object detection and tracking in satellite images
Xiao, F., Yuan, F., and Cheng, E. Detection and tracking method of maritime moving
targets based on geosynchronous orbit satellite optical images. Electronics, 9(7):1–19,
July 2020. URL http://dx.doi.org/10.3390/electronics9071092
34. Forest smoke detection
Wang, G., Li, J., Zheng, Y., Long, Q., and Gu, W. Forest smoke detection based on
deep learning and background modeling. In IEEE International Conference on Power,
Intelligent Computing and Systems (ICPICS), pages 112–116. Shenyang, China, July
2020. URL http://dx.doi.org/10.1109/ICPICS50287.2020.9202287
35. Vehicle counting
Pratama, Y. and Ratno, P. Multithreading application for counting vehicle by using
background subtraction method. Indonesian Journal of Computing and Cybernetics
Systems, 14(3):309–318, July 2020. URL http://dx.doi.org/10.22146/ijccs.57594
4
36. Crowd abnormal behavior detection
Sonkar, R., Rathod, S., Jadhav, R., and Patil, D. Crowd abnormal behaviour detec-
tion using deep learning. In International Conference on Automation, Computing and
Communication (ICACC), pages 1–5. July 2020. URL http://dx.doi.org/10.1051/
itmconf/20203203040
37. Detection of football players with a thermal camera
Cioppa, A., Deliège, A., Ul Huda, N., Gade, R., Van Droogenbroeck, M., and Moeslund,
T. Multimodal and multiview distillation for real-time player detection on a football
field. In IEEE International Conference on Computer Vision and Pattern Recognition
Workshops (CVPRW), CVsports, pages 3846–3855. Seattle, Washington, USA, June
2020. URL http://dx.doi.org/10.1109/CVPRW50498.2020.00448
38. Fault detection of field equipment
Wu, C., Guo, S., Wu, Y., Ai, J., and Xiong, N. Networked fault detection of field
equipment from monitoring system based on fusing of motion sensing and appearance
information. Multimedia Tools and Applications, 79:16319–16348, June 2020. URL
http://dx.doi.org/10.1007/s11042-020-08885-8
39. Fall detection
Mohmoodzadeh, A., Agahi, H., and Vaghefi, M. A fall detection system based on the
type II fuzzy logic and multi-objective PSO algorithm. Signal and Data Processing,
17(1):47–60, 2020. URL http://jsdp.rcisp.ac.ir/browse.php?a_id=886&sid=1&
slc_lang=en
40. Smoke vehicle detection
Tao, H. and Lu, X. Smoke vehicle detection based on multi-feature fusion and hidden
Markov model. Journal of Real-Time Image Processing, 17:745–758, 2020. URL http:
//dx.doi.org/10.1007/s11554-019-00856-z
41. Traffic flow analysis using thermopile array sensors
Zhang, Y. and Yang, B. Traffic flow detection using thermopile array sensor. IEEE
Sensors Journal, 20(10):5155–5164, May 2020. URL http://dx.doi.org/10.1109/
JSEN.2020.2968090
42. Traffic surveillance
Zeng, W., Xie, C., Yang, Z., and Lu, X. A universal sample-based background sub-
traction method for traffic surveillance videos. Multimedia Tools and Applications,
79:22211–22234, May 2020. URL http://dx.doi.org/10.1007/s11042-020-08948-w
43. Handling of blurred video frames
Bokaei, M. and Razavikia, S. Robust low rank and sparse decomposition from blurred
video frames. TechRxiv, April 2020. URL http://dx.doi.org/10.36227/techrxiv.
12199094
44. Crowd gathering and commotion detection
Yang, D.S., Liu, C.Y., Liao, W.H., and Ruan, S.J. Crowd gathering and commotion
detection based on the stillness and motion model. Multimedia Tools and Applications,
79:19435–19449, March 2020. URL http://dx.doi.org/10.1007/s11042-020-08827-4
5
45. Elderly fall detection
Khraief, C., Benzarti, F., and Amiri, H. Elderly fall detection based on multi-stream
deep convolutional networks. Multimedia Tools and Applications, 79:19537–19560, March
2020. URL http://dx.doi.org/10.1007/s11042-020-08812-x
46. Foreground detection of RGB-D images with a NVIDIA Jetson
Janus, P., Kryjak, T., and Gorgon, M. Foreground object segmentation in RGB-D
data implemented on GPU. CoRR, abs/2002.00250, February 2020. URL https:
//arxiv.org/abs/2002.00250
47. Real-time vehicle counting system
Varghese, A. and Sreelekha, G. A robust, low-complexity real-time vehicle counting
system for automated traffic surveillance. In National Conference on Communications
(NCC), pages 1–6. Kharagpur, India, February 2020. URL http://dx.doi.org/10.
1109/NCC48643.2020.9056045
48. Detection of smoky vehicles from traffic surveillance videos
Tao, H. Detecting smoky vehicles from traffic surveillance videos based on dynamic
features. Applied Intelligence, 49:1–16, December 2019. URL http://dx.doi.org/10.
1007/s10489-019-01589-z
49. White light interference fringe detection
Hu, M., Li, H., Li, H., and Li, K. White light interference fringe detection based on
improved ViBE algorithm. In Symposium on Novel Optoelectronic Detection Technology
and Applications, volume 114553A of Proceedings of SPIE. SPIE, December 2019. URL
http://dx.doi.org/10.1117/12.2564568
50. Hardware implementation for object tracking
Wijesinghe, Y., Samarawickrama, J., and Dais, D. Hardware and software co-design
for object detection with modified ViBe algorithm and particle filtering based object
tracking. In Conference on Industrial and Information Systems (ICIIS), pages 506–511.
Kandy, Sri Lanka, December 2019. URL http://dx.doi.org/10.1109/ICIIS47346.
2019.9063249
51. Elderly fall detection
Khraief, C., Benzarti, F., and Amiri, H. Convolutional neural network based on dynamic
motion and shape variations for elderly fall detection. International Journal of Machine
Learning and Computing,, 9(6):814–820, December 2019. URL http://dx.doi.org/
10.18178/ijmlc.2019.9.6.878
52. Detection of vehicles
Jiang, K. and Wang, J. Research on improved adaptive vibe algorithm for vehicle detec-
tion. International Journal of Advanced Network, Monitoring and Controls, 4(4):11–17,
2019. URL http://dx.doi.org/10.21307/ijanmc-2019-065
53. Fast detection and tracking of pedestrians
Wang, L., Gui, J., Lu, Z.M., and Liu, C. Fast pedestrian detection and tracking based
on ViBe combined HOG-SVM scheme. International Journal of Innovative Computing,
Information and Control, 15(6):2305–2320, December 2019. URL http://dx.doi.org/
10.24507/ijicic.15.06.2305
6
54. Multiple object tracking
Sheng, H., Zhang, Y., Chen, J., Xiong, Z., and Zhang, J. Heterogeneous association
graph fusion for target association in multiple object tracking. IEEE Transactions on
Circuits and Systems for Video Technology, 29(11):3269–3280, November 2019. URL
http://dx.doi.org/10.1109/TCSVT.2018.2882192
55. Vehicle detection
Yuan, S. and Jin, H. Vehicle detection using cascaded feature based on improved PBAS
algorithm. Computer Application Research, 36(11):1–8, November 2019. URL http:
//dx.doi.org/i10.3969/j.issn.1001-3695.2018.05.0340
56. Detection of river contaminant by UAV
Lin, Y., Zhu, Y., Shi, F., Yu, J., Huang, P., and Hou, D. Image processing techniques
for UAV vision-based river floating contaminant detection. In Chinese Automation
Congress (CAC), pages 89–94. Hangzhou, China, November 2019. URL http://dx.
doi.org/10.1109/CAC48633.2019.8997182
57. Detection of jaywalkers
Tomas, J., Jocsing, S., Guanzon, J., and Matias, C. Effectiveness of haar-like features
and vibe algorithm for detecting jaywalkers. In International Conference on Compu-
tational Intelligence and Intelligent Systems (CCIS), pages 90–98. Bangkok, Thailand,
November 2019. URL http://dx.doi.org/10.1145/3372422.3372436
58. Automatic identification of ships from videos taken by a UAV
Zhou, F., Pan, S., and Jiang, J. Verification of AIS data by using video images taken
by a UAV. The Journal of Navigation, 72(6):1345–1358, November 2019. URL http:
//dx.doi.org/10.1017/S0373463319000262
59. Intrusion detection at railway crossings
Cai, N., Chen, H., Li, Y., and Peng, Y. Intrusion detection and tracking at railway
crossing. In International Conference on Artificial Intelligence and Advanced Manufac-
turing (AJAM), pages 1–6. Dublin, Ireland, October 2019. URL http://dx.doi.org/
10.1145/3358331.3358388
60. Smoke detection in videos
Wang, Y., Cheng, J., Liu, T., and a nd Y. Xiong, Y.Z. Smoke video detection based on
lightweight convolutional neural network. In International Conference on Electronic In-
formation Technology and Computer Engineering (EITCE), pages 1462–1466. Xiamen,
China, October 2019. URL http://dx.doi.org/10.1109/EITCE47263.2019.9095138
61. Surveillance of elevator cabs
Sun, Z., Xu, B., wu, D., Lu, M., and Cong, J. A real-time video surveillance and
state detection approach for elevator cabs. In International Conference on Control,
Automation and Information Sciences (ICCAIS), pages 1–6. Chengdu, China, October
2019. URL http://dx.doi.org/10.1109/ICCAIS46528.2019.9074707
62. Detection of swimmers’ motion
Hayat, M., Yang, G., Iqbal, A., Saleem, A., Hussain, A., and Mateen, M. The swim-
mers motion detection using improved VIBE algorithm. In International Conference
7
on Robotics and Automation in Industry (ICRAI), pages 1–6. Rawalpindi, Pakistan,
October 2019. URL http://dx.doi.org/10.1109/ICRAI47710.2019.8967390
63. Video based fire detection in photovoltaic systems
He, Z. Video based fire detection in photovoltaic system. In International Conference
on Mechanical, Control and Computer Engineering (ICMCCE), pages 289–293. Hohhot,
China, October 2019. URL http://dx.doi.org/10.1109/ICMCCE48743.2019.00072
64. Background analysis for coding
Wu, Q., Sun, T., Jiang, X., Xu, K., Xu, Q., and He, P. HEVC double compression de-
tection with non-aligned GOP structures based on a fusion feature with optical flow and
prediction units. In International Congress on Image and Signal Processing, BioMedical
Engineering and Informatics (CISP-BMEI), pages 1–6. Suzhou, China, October 2019.
URL http://dx.doi.org/10.1109/CISP-BMEI48845.2019.8965766
65. Semi-automatic annotation for vehicle detection
Feng, R.C., Lin, D.T., Chen, K.M., Lin, Y.Y., and Liu, C.D. Improving deep learning by
incorporating semi-automatic moving object annotation and filtering for vision-based
vehicle detection. In IEEE International Conference on Systems, Man, and Cybernetics
(SMC), pages 2484–2489. Bari, Italy, October 2019. URL http://dx.doi.org/10.
1109/SMC.2019.8914169
66. Detection of mesh fabric defects
Liu, X., Feng, Q., Du, Y., Xu, J., Yan, H., Tong, L., Chen, X., and Zheng, D. A
method for detecting mesh fabric defects with improved ViBe. Journal of Xi’an Poly-
technic University, 33(5):511–516, October 2019. URL http://dx.doi.org/10.13338/
j.issn.1674-649x.2019.05.007
67. Crowd analysis
Pandey, M., Singhal, S., and Tripathi, V. An efficient vision-based group detection
framework in crowded scene. In Frontiers in Intelligent Computing: Theory and Appli-
cations, volume 1014 of Advances in Intelligent Systems and Computing, pages 201–209.
Springer, October 2019. URL http://dx.doi.org/10.1007/978-981-13-9920-6_21
68. Fire detection
Jin, S. and Lu, X. Vision-based forest fire detection using machine learning. In Interna-
tional Conference on Computer Science and Application Engineering (CSAE), pages 1–
6. Sanya, China, October 2019. URL http://dx.doi.org/10.1145/3331453.3361659
69. Smoke detection
Cao, Y. and Lu, X. Learning spatial-temporal representation for smokevehicle detection.
Multimedia Tools and Applications, 78(19):27871–27889, October 2019. URL http:
//dx.doi.org/10.1007/s11042-019-07926-1
70. Forest fire smoke detection
Gao, Y. and Cheng, P. Forest fire smoke detection based on visual smoke root and
diffusion model. Fire detection, 55(5):1801–1826, September 2019. URL http://dx.
doi.org/10.1007/s10694-019-00831-x
8
71. Anomalous event detection and localization
Bansod, S. and Nanadedkar, A. Anomalous event detection and localization using
stacked autoencoder. In International Conference on Computer Vision and Image Pro-
cessing (CVIP), volume 1148 of Communications in Computer and Information Sci-
ence, pages 117–129. Springer, September 2019. URL http://dx.doi.org/10.1007/
978-981-15-4018-9_11
72. IoT for surveillance
Sultana, T. and Wahid, K. IoT-Guard: Event-driven fog-based video surveillance system
for real-time security management. IEEE Access, 7:134881–134894, September 2019.
URL http://dx.doi.org/10.1109/ACCESS.2019.2941978
73. Abnormal behavior detection
Wang, Y., Luo, J., and Wang, D. Abnormal behavior detection algorithm based on
weighted amplitude direction angle entropy of key frame. Computer and Digital En-
gineering, 9:2281–2285, September 2019. URL http://caod.oriprobe.com/articles/
57399074/Abnormal_Behavior_Detection_Algorithm_Based_on_Weighted_Amplitude_
Dire.htm
74. Radar tracking by fusion with a camera
Zhang, R. and Cao, S. Extending reliability of mmWave radar tracking and detection
via fusion with camera. IEEE Access, 7:137065–137079, September 2019. URL http:
//dx.doi.org/10.1109/ACCESS.2019.2942382
75. Detection of intrusions along railway lines
Qu, Z., Yi, W., Zhou, R., and Wang, H. Scale self-adaption tracking method of defog-
PSA-Kcf defogging and dimensionality reduction of foreign matter intrusion along rail-
way lines. IEEE Access, 7:126720–126733, September 2019. URL http://dx.doi.org/
10.1109/ACCESS.2019.2939435
76. Single-pixel imaging
Ye, Z., Su, B., Qiu, P., and Gao, W. Secured regions of interest (SROIs) in single-pixel
imaging. Scientific Reports, 9(1):1–8, September 2019. URL http://dx.doi.org/10.
1038/s41598-019-49282-y
77. Creation of video tubes
Ruan, T., Wei, S., Li, J., and Zhao, Y. Rearranging online tubes for streaming video
synopsis: A dynamic graph coloring approach. IEEE Transactions on Image Process-
ing, 28(8):3873–3884, August 2019. URL http://dx.doi.org/10.1109/TIP.2019.
2903322
78. Detection of moving vehicles
Xia, X., Lu, X., Cao, Y., Xia, S., and Fu, C. Moving vehicle detection with shadow
elimination based on improved ViBe algorithm. Journal of Physics: Conference Se-
ries, 1302:1–7, August 2019. URL http://dx.doi.org/10.1088/1742-6596/1302/2/
022080
79. Forgery detection in videos for foreground removal
Su, L., Luo, H., and Wang, S. A novel forgery detection algorithm for video foreground
9
removal. IEEE Access, 7:109719–109728, August 2019. URL http://dx.doi.org/10.
1109/ACCESS.2019.2933871
80. Vehicle traffic statistics of video taken by UAVs
Lu, M. and Tang, Z. Implementation of vehicle traffic statistics algorithm based on
ViBe image processing. In Materials Science and Engineering, volume 569 of Conference
Series, pages 1–6. IOP, 2019. URL http://dx.doi.org/10.1088/1757-899X/569/5/
052033
81. Smoke detection
Liu, Z., Yang, X., Liu, Y., and Qian, Z. Smoke-detection framework for high-definition
video using fused spatial- and frequency-domain features. IEEE Access, 7:89687–89701,
July 2019. URL http://dx.doi.org/10.1109/ACCESS.2019.2926571
82. Landslide detection based on a Raspberry Pi
Mishra, P., Dhar, S., and Kalra, M. Landslide detection system using computer vi-
sion approach and Raspberry Pi. In International Conference on Communication and
Electronics Systems (ICCES), pages 1201–1206. Coimbatore, India, July 2019. URL
http://dx.doi.org/10.1109/ICCES45898.2019.9002256
83. Robot grabbing
Liu, S., Huang, J., Shen, Y., and Guo, Z. Application of improved VIBE algorithm in
robot grabbing system based on visual servo. In International Conference on Robotics,
Control and Automation (ICRCA), pages 105–110. Guangzhou, China, July 2019. URL
http://dx.doi.org/0.1145/3351180.3351200
84. Building a dataset for training a fish detector
Konovalov, D., Saleh, A., Bradley, M., Sankupellay, M., Marini, S., and Sheaves, M.
Underwater fish detection with weak multi-domain supervision. In International Joint
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