Moving Object Detection using Intelligent Spectaculars

Abstract

Abstract: Moving Object detection systems are used to identify and locate objects in images or videos. When used spectacles, an object detection system can allow the user to see information about the objects in their field of view. This can be useful in a variety of applications, such as helping blind people navigate their environment, or providing augmented reality information to workers. Region-based Convolutional Neural Networks (RCNN) is a type of machine learning model that is commonly used for object detection. The RCNN model first uses a convolutional neural network (CNN) to extract features from the input image, and then applies a region proposal algorithm to identify potential object regions in the image. These regions are then fed into a second CNN, which classifies the regions as objects or background. The RCNN model has been shown to be effective at detecting a wide range of objects in images and videos.