One popular approach for object detection is Haar cascades, which use machine learning techniques to identify specific patterns or features of objects. This method involves training a classifier using positive and negative samples, enabling it to detect objects based on these learned features. Haar cascades have been successfully applied in face detection, where the classifier learns to recognize facial features like eyes, nose, and mouth.