Dense optical flow based background subtraction technique for object segmentation in moving camera environment
| العنوان: | Dense optical flow based background subtraction technique for object segmentation in moving camera environment |
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| المؤلفون: | Om Prakash, Manish Khare, Arati Kushwaha, Ashish Khare |
| المصدر: | IET Image Processing. 14:3393-3404 |
| بيانات النشر: | Institution of Engineering and Technology (IET), 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Background subtraction, Pixel, Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Optical flow, 020206 networking & telecommunications, 02 engineering and technology, Image segmentation, Thresholding, Object detection, symbols.namesake, Computer Science::Computer Vision and Pattern Recognition, Signal Processing, 0202 electrical engineering, electronic engineering, information engineering, symbols, 020201 artificial intelligence & image processing, Computer vision, Segmentation, Computer Vision and Pattern Recognition, Artificial intelligence, Electrical and Electronic Engineering, business, Gaussian process, Software |
| الوصف: | Segmentation of moving object in video with moving background is a challenging problem and it becomes more difficult with varying illumination. The authors propose a dense optical flow-based background subtraction technique for object segmentation. The proposed technique is fast and reliable for segmentation of moving objects in realistic unconstrained videos. In the proposed work, they stabilise the camera motion by computing homography matrix, then they perform statistical background modelling using single Gaussian background modelling approach. Moving pixels are identified using dense optical flow in the background modelled scenario. The dense optical flow provides motion information of each pixel between consecutive frames, therefore for moving pixel identification they compute motion flow vector of each pixel between consecutive frames. To distinguish between foreground and background pixels, they labelled each pixel and thresholding the magnitude of motion flow vector identifies the moving pixels. The effectiveness of the proposed algorithm has been evaluated both qualitatively and quantitatively. The proposed algorithm has been evaluated on several realistic videos of different complex conditions. To assess the performance of the proposed work, the authors compared their algorithm with other state-of-art methods and found that the proposed method outperforms the other methods. |
| تدمد: | 1751-9667 1751-9659 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::43f748fb9939add46945b4cc08763184 https://doi.org/10.1049/iet-ipr.2019.0960 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........43f748fb9939add46945b4cc08763184 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 17519667 17519659 |
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