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 automated vehicle parking systems.
You can detect objects using a variety of models, including:
Other methods for detecting objects with computer vision include using gradient-based, derivative-based, and template matching approaches.
See also: Steve on Image Processing, image processing and computer vision, MATLAB and OpenCV, object recognition, face recognition, image recognition, Feature Extraction, Stereo Vision, Optical Flow, ransac, pattern recognition, object detection videos, point cloud, deep learning