Smart Household Object Detection Using CNN

Abstract

Object detection is one of the most basic and central tasks in computer vision. object detection is a subset of object recognition. Its task is to find all the interested objects in the image, and determine the category and location of the objects. Object detection is widely used and has strong practical value and research prospects. Applications include face detection, pedestrian detection and vehicle detection. In recent years, with the development of convolutional neural network, significant breakthroughs have been made in object detection. This work aim to detect objects in the video frames. It detects household objects and predicts the object where it may be present. Convolutional Neural Networks (CNN) is used to detect objects in the environment. Then Resnet50 is used to classify the images into objects. Then Support vector machine (SVM) is used to train objects and stored in object database. It will be retrieved whenever neural networks sent object for verification.