Literature Review on Background Subtraction Model for Object Detection
| Autor: | Singh, Jaskirat, Kumar Sahoo, Sandeep |
|---|---|
| Přispěvatelé: | University of Alberta, university of alberta, sahoo, sandeep |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Spatially-varying sensing
Video Processing Image Processing Computer Vision ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Fish-eye lenses [INFO] Computer Science [cs] adaptive training virtual games rehabilitation Machine Learning Pose detection Action Recognition virtual reality [INFO]Computer Science [cs] CNN |
| Zdroj: | [Research Report] university of alberta. 2021 |
| Popis: | Background subtraction is widely used technique in computer vision application for object detection and segmentation. Most of the work done on background subtraction considers static camera that identify moving objects by detecting areas in a video that change over time, which is not applicable in real world scenarios like moving camera mounted on the autonomous vehicle.it's a difficult problem due to the motion of both camera and the object.In this paper, we extend the concept of subtracting areas at rest to apply to video captured from a freely moving camera. we approach this problem by exploiting optical flow based background subtraction method. |
| Databáze: | OpenAIRE |
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