Real Time Object Detection Using OpenCV

Abstract

Object detection has evolved into a vital component of intelligent vision systems. It involves identifying instances of objects from specific categories in digital images or videos. This paper presents a real-time object detection approach using the Single Shot Multibox Detector (SSD) model with a MobileNet backbone, optimized for speed and low-resource devices. Implemented using OpenCV and TensorFlow, the system supports both still images and live video input. The model demonstrates an effective balance between speed and accuracy, offering high detection precision on standard computing hardware. Applications include surveillance, autonomous systems, and industrial monitoring, where real-time object detection is crucial. Keywords: Real-Time Detection, SSD (Single Shot Multibox Detector), MobileNet, Deep Learning, OpenCV, Computer Vision.