EE5731_Questions_updated_11-11

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According to the lecture notes, why is the naive solution to face detection not preferred? (a) It requires the images to be preprocessed into a standardized size which can lead to loss of detail. (b) It is too slow for practical use due to the extensive computation required for each subwindow. (c) It can only detect faces that are directly looking at the camera and not in profile view. (d) It only uses the AdaBoost algorithm without any additional optimizations for speed. Justify your answer. (b) It is too slow for practical use due to the extensive computation required for each subwindow. Justification: The naive approach to face detection would require evaluating every possible position and size of a subwindow across the entire image, which would be computationally intensive and too slow for real-time applications. This is why optimizations like integral images and classifier cascades are necessary. Integral Image in Face Detection In the context of face detection using integral images, which of the following statements are true? (a) The integral image is computed to simplify the pixel summation process within rectangular regions of the image. (b) The algorithm requires the original image to be converted to a specific size before computing the integral image. (c) Generating square windows starting from 24x24 pixels is the first step in the face detection process after computing the integral image. (d) The integral image is used to decrease the number of features that need to be computed, thus speeding up the process. Justify your answer. (a) The integral image is computed to simplify the pixel summation process within rectangular regions of the image. Justification: An integral image allows for the rapid calculation of the sum of pixel values within any rectangular region of an image. This is beneficial for feature calculation as it can be done in constant time regardless of the size of the region. (c) Generating square windows starting from 24x24 pixels is the first step in the face detection process after computing the integral image. Justification: The face detection process typically starts with a standard window size, such as 24x24 pixels, to scan the image for potential faces. This window is then scaled to detect faces at different sizes. Cascade of Classifiers Which of the following statements correctly describe the cascade of classifiers in face detection?

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