Background Subtraction — MCQs | Digital Image Processing

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1. Who is primarily responsible for identifying moving objects from static scenes in video surveillance?



2. Which technique assumes that background remains nearly constant over time?



3. Which of the following is a key application of background subtraction?



4. What is typically subtracted in background subtraction techniques?



5. Which method updates the background model over time to adapt to scene changes?



6. What is the purpose of a learning rate in adaptive background subtraction?



7. Which statistical method is often used for adaptive background modeling?



8. Which problem does background subtraction aim to overcome in video analysis?



9. Which of the following can affect the accuracy of background subtraction?



10. In a Gaussian Mixture Model, what does each Gaussian component represent?



11. Which of the following is a challenge in background subtraction?



12. Which metric is commonly used to compare the current frame with the background model?



13. What operation is commonly applied after subtraction to clean up the foreground mask?



14. Which condition can lead to ghost artifacts in background subtraction?



15. What is the initial step in any background subtraction method?



16. Which background subtraction technique uses statistical learning?



17. Which condition is most ideal for simple background subtraction?



18. What does a high learning rate in adaptive modeling result in?



19. Which technique can help reduce shadows in foreground masks?



20. What role does thresholding play in background subtraction?



21. What type of noise affects background subtraction in outdoor environments?



22. Why is frame differencing less robust than background modeling?



23. Which frame is used to initialize the background in a basic model?



24. Which component helps identify whether a pixel belongs to foreground or background?



25. Which filter is often used to reduce noise before thresholding the foreground mask?



26. Which term describes objects that appear in the foreground mask but are not real motion?



27. Which method performs subtraction between consecutive frames?



28. What is the output of background subtraction?



29. Which element is crucial for background subtraction in moving camera setups?



30. Which background subtraction approach is suitable for long-term outdoor surveillance?



31. Which property allows GMM to handle multimodal backgrounds?



32. Which term defines the process of updating the background image?



33. What kind of pixel changes are typically labeled as foreground?



34. What is a common drawback of using high thresholds in subtraction?



35. Which method is more suitable for real-time processing?



36. What does a low learning rate cause in adaptive modeling?



37. Which data structure can efficiently store background models in real-time systems?



38. How can we suppress noise in the foreground mask?



39. What is typically used to evaluate the performance of a background subtraction algorithm?



40. Which color space transformation helps in handling illumination variations?



41. Why is shadow detection important in background subtraction?



42. What is the impact of camera jitter on background subtraction?



43. Which method uses probability to classify pixels into foreground and background?



44. Which algorithm is used for adaptive background modeling in OpenCV?



45. What does the acronym MOG stand for in background subtraction?



46. Which foreground detection issue arises from objects with similar color as the background?



47. What is the ideal condition for foreground extraction in video?



48. What is the foreground mask composed of?



49. Which of the following is not typically a part of background subtraction?



50. What challenge does weather introduce to background subtraction?



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