The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Moving object tracking using optical flow and motion vector estimation
Abstract
Moving object detection and tracking is an evolving research field due to its wide applications in traffic surveillance, 3D reconstruction, motion analysis (human and non-human), activity recognition, medical imaging etc. However real time object tracking is a challenging task due to dynamic tacking environment and different limiting parameters like view point, anthropometric variation, dimensions of an object, cluttered background, camera motions, occlusion etc. In this paper, we have developed new object detection and tracking algorithm which makes use of optical flow in conjunction with motion vector estimation for object detection and tracking in a sequence of frames. The optical flow gives valuable information about the object movement even if no quantitative parameters are computed. The motion vector estimation technique can provide an estimation of object position from consecutive frames which increases the accuracy of this algorithm and helps to provide robust result irrespective of image blur and cluttered background. The use of median filter with this algorithm makes it more robust in the presence of noise. The developed algorithm is applied to wide range of standard and real time datasets with different illumination (indoor and outdoor), object speed etc. The obtained results indicates that the developed algorithm over performs over conventional methods and state of art methods of object tracking.
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“They are useful in applications focused on movement patterns, such as monitoring crowd flows in and out.”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [60]
Citations
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1 retracted
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Performance of optical flow techniques
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Optical Flow Based Moving Object Detection And Tracking For Traffic Surveillance
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A Survey on Object Detection and Tracking Methods
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A Survey on Object Detection and Tracking Methods
Parekh, H. S., Thakore, D. G., & Jaliya, U. K. (2014) · International Journal of Innovative Research in Computer and Communication Engineering · Cited by 104
Object Tracking With Only Background Cues
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A method of object tracking based on particle filter and optical flow to avoid degeneration problem
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Efficient Fast Object-Tracking Scheme Based on Motion-vector-located Pattern Match
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Research works printed but not linked: 1
- shantaiya, 2015, Multiple Object Tracking using Kalman Filter and Optical Flow, European Journal of Advances in Engineering and Technology, 2, 34
Cited by
Vehicle Tracking and Speed Estimation from Traffic Videos
Hua, S., Kapoor, M., & Anastasiu, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2018.00028 · Cited by 84
Review of optical flow technique for moving object detection
Agarwal, A., Gupta, S., & Singh, D. K. (2016) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i.2016.7917999 · Cited by 74
Human detection techniques for real time surveillance: a comprehensive survey
Ansari, M. A., & Singh, D. K. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-10103-4 · Cited by 57
Wutke, M., Heinrich, F., Das, P. P., Lange, A., Gentz, M., Traulsen, I., Warns, F. K., Schmitt, A. O., & Gültaş, M. (2021) · Sensors · doi:10.3390/s21227512 · Cited by 56
Vehicle Detection Algorithms for Autonomous Driving: A Review
Liang, L., Ma, H., Zhao, L., Xie, X., Hua, C., Zhang, M., & Zhang, Y. (2024) · Sensors · doi:10.3390/s24103088 · Cited by 64
Metadata
- Authors
- Kale, K., Pawar, S., & Dhulekar, P.
- Affiliations
- Savitribai Phule Pune University (IN)
- Venue
- 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)
- Publisher
- IEEE
- Published
- 2015-09
- Pages
- 1-6
- OpenAlex
- W2221502561
- Cited by
- 103
- References
- 10
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 15 · 2023: 21 · 2022: 9 · 2021: 8 · 2020: 17 · 2019: 6 · 2018: 7 · 2017: 5 · 2016: 4
- FWCI
- 2.19
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- moving object tracking, moving object detection, optical flow, motion vector estimation, real-time tracking, median filter, noise robustness, background clutter, occlusion, traffic monitoring
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