Efficient method for detecting and tracking moving objects in video
| Autor: | Nilesh J. Uke, Pravin R. Futane |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry 3D single-object recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Corner detection Motion detection Object detection Object-class detection Motion estimation Video tracking Viola–Jones object detection framework Computer vision Artificial intelligence business |
| Zdroj: | 2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT). |
| Popis: | Detection and tracking of moving object in the video has turned into a fascinating zone of exploration in the field of computer vision and has wide applications in fields like video surveillance, service robots, public security and target recognition. Although researches have proposed many approaches for object detection, robustness remains a huge challenge. In this paper, we proposed hybrid method of object detection using motion estimation and tracking by parallel kalman filter. Detection of the moving object is performed by analyzing the moving parts by corner and the shape feature extraction. The parallel kalman filter is used to tracks the object that is detected by calculating the motion estimation in video. The object tracking using the shape and the corner feature helps in providing the extract tracking of the object. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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