Data Science and Machine Learning (Theory and Projects) A to Z - Object Detection: Person Detection

Data Science and Machine Learning (Theory and Projects) A to Z - Object Detection: Person Detection

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Information Technology (IT), Architecture, Other

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The video tutorial discusses the desirable properties of an ideal object detector, focusing on shift, scale, and rotation invariance. It explains how these invariances can be achieved using methods like sliding windows, Gaussian pyramids, and data augmentation. The tutorial introduces the Histogram of Oriented Gradients (HOG) method for person detection, based on the work of Dalal and Triggs. It details the HOG feature extraction process and the use of Support Vector Machines (SVM) for classification. The video also covers the practical application of HOG, including scaling and bounding box detection, highlighting its significance in pedestrian detection.

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OPEN ENDED QUESTION

3 mins • 1 pt

What new insight or understanding did you gain from this video?

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