The week's pick
Reseach Article
An Inspection of Object Classification for Tracking Fast-Moving Object
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 185 - Number 19 |
| Year of Publication: 2023 |
| Authors: Daniel Mohammed, Solomon Kweku-Duah, Joseph Bonney |
10.5120/ijca2023922850
|
Daniel Mohammed, Solomon Kweku-Duah, Joseph Bonney . An Inspection of Object Classification for Tracking Fast-Moving Object. International Journal of Computer Applications. 185, 19 ( Jun 2023), 11-13. DOI=10.5120/ijca2023922850
Abstract
Vision is important in life; in earlier years many systems fail because of poor classification. Objects can be classified as living or man-made movable objects such as a human, vehicles, animals, floating clouds, and swaying trees in the field of computer vision. Many algorithms have been proposed for classification from the image of a video stream. For robust and accurate tracking, it also depends on a good classification algorithm that segments foregrounds from a background in a video stream. The goal of object classification is to extract useful information from images pinpointing between static and moving objects. In this paper, different types of classification algorithms are discussed, and tracking techniques are proposed in the field of computer vision. The goal of tracking is not achieved without the classification of objects.
References
- P. K. Mishra and G. Saroha, "A Study on Classification for Static and Moving Object in Video Surveillance System," 2016.
- H. S. Parekh, D. G. Thakore, and U. K. Jaliya, "A survey on object detection and tracking methods," International Journal of Innovative Research in Computer and Communication Engineering, vol. 2, pp. 2970-2979, 2014.
- S. C. Sen-Ching and C. Kamath, "Robust techniques for background subtraction in urban traffic video," in Electronic Imaging 2004, 2004, pp. 881-892.
- C. Sukanya, R. Gokul, and V. Paul, "A Survey on Object Recognition Methods," International Journal of Science, Engineering and Computer Technology, vol. 6, p. 48, 2016.
- S. Brutzer, B. Höferlin, and G. Heidemann, "Evaluation of background subtraction techniques for video surveillance," in Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, 2011, pp. 1937-1944.
- S. H. Shaikh, K. Saeed, and N. Chaki, "Moving Object Detection Approaches, Challenges, and Object Tracking," in Moving Object Detection Using Background Subtraction, ed: Springer, 2014, pp. 5-14.
- J. Heikkilä and O. Silvén, "A real-time system for monitoring of cyclists and pedestrians," Image and Vision Computing, vol. 22, pp. 563-570, 2004.
- U. Joshi and K. Patel, "Object tracking and classification under illumination variations," 2016.
- M. Asgarizadeh, H. Pourghassem, G. Shahgholian, and H. Soleimani, "Robust and real-time object tracking using regional mutual information in surveillance and reconnaissance systems," in 2011 7th Iranian Conference on Machine Vision and Image Processing, 2011, pp. 1-5.
- P. K. Mishra and G. Saroha, "A study on classification for a static and moving object in video surveillance system," International Journal of Image, Graphics, and Signal Processing, vol. 8, p. 76, 2016.
- P. Gehler and S. Nowozin, "On feature combination for multiclass object classification," in Computer Vision, 2009 IEEE 12th International Conference on, 2009, pp. 221-228.
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