Approximate Contours and Convex Hull for Self Driving Car Collision Avoidance

Опубликовано: 11 Октябрь 2024
на канале: The AI University

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This video titled "Approximate Contours and Convex Hull for Self Driving Car Collision Avoidance" explains the concept of Approximating Contours and Convex Hull that is widely used in collision avoidance for self-driving cars. It also shows a practical implementation using Python Language and OpenCV module. Hull means the exterior or the shape of the object. Therefore, the Convex Hull of a shape is a tight-fitting convex boundary around the points or the shape. A lot of contours that we encounter in real life are noisy in nature and One way to handle it would be to get all the points on the contour and then approximate it with a smooth polygon. One can approximate the contours with the help of various thresholds or accuracies,
you will see the contours changing their shapes. Threshold or accuracy
factor helps in smoothening the contour shape better. The convex hull looks at the outer edges of the shape or object and draws lines to each edge. In a way creating the smallest polygon which can fit around the shape of an object. In other words, Given a set of points in the plane. the convex hull of the set is the smallest convex polygon that contains all the points of it.

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