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OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos.From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Headless software (e.g. "headless Linux", [1]) is software capable of working on a device without a graphical user interface. Such software receives inputs and provides output through other interfaces like network or serial port and is common on servers and embedded devices .
Headless CMS is a content management system (CMS) without a pre-built front-end presentation layer or templating system; instead, it provides a content repository and an API for managing the content. While this allows for greater flexibility and customizability, it can also present challenges or drawbacks for teams and organizations. [11]
The Harris corner detector is a corner detection operator that is commonly used in computer vision algorithms to extract corners and infer features of an image. It was first introduced by Chris Harris and Mike Stephens in 1988 upon the improvement of Moravec's corner detector. [1]
The system also allows a user to leave the ignition key in the vehicle, for later retrieval — including by another user sharing a unique entry code. Two hikers, for example, can leave the keys in the glove box, lock the door, and either hiker can return later to access the vehicle via their own code.
An example image thresholded using Otsu's algorithm Original image. In computer vision and image processing, Otsu's method, named after Nobuyuki Otsu (大津展之, Ōtsu Nobuyuki), is used to perform automatic image thresholding. [1]