Object detection is the process of finding instances of real-world objects such as faces, bicycles, and buildings in images or videos. Object detection algorithms typically use extracted features and learning algorithms to recognize instances of an object category. It is commonly used in applications such as image retrieval, security, surveillance, and advanced driver assistance systems (ADAS).
You can detect objects using a variety of models, including:
- Deep learning object detection
- Feature-based object detection
- Viola-Jones object detection
- SVM classification with histograms of oriented gradients (HOG) features
- Image segmentation and blob analysis