Object detection deals with recognizing the presence of objects of a certain semantic class (e.g. “humans”, “buildings”, “cars”, &c) in digital image and video data.
Object detection is the branch of computer vision and image-processing that deals with recognizing objects of a certain semantic class (e.g. “humans”, “buildings”, “cars”, &c) as present within image and video data. Well-researched subdomains of object detection include face-detection and pedestrian detection.
Most contemporary algorithms for object detection employ some mode of image feature-extraction – such as sift or haar-wavelet – coupled with a machine-learning scheme for deriving meaning from the extracted and quantified image features.
Object detection has myriad applications, across many related computer-vision disciplines: content-based image retrieval (or cbir), optical character recognition (or ocr), image recognition, and automated video surveillance.
