Abstract
Object recognition, a small branch of computer vision, deals with making computers detect and analyze objects in either a picture, a saved video, or a real time video feed. The major challenge in the task of object recognition is obtaining efficiency. There are several object recognition algorithms currently in place which provide astonishing results with varying efficiency. There are several libraries in the world today that provide implemented solutions to help with applications concerning object recognition; two of the most popular of these libraries are OpenCV and TensorFlow. This research focuses on two broad aspects – understanding the working of neural networks, more specifically, convolutional neural networks by experimenting with different models for object classification that use them and implementing real time object detection using pre-trained models and machine learning libraries.
Advisor
Fox, Nathan
Department
Computer Science; Mathematics
Recommended Citation
Bhalodi, Bhargav Anandkumar, "3D Object Recognition in Real Time Using Machine Learning" (2019). Senior Independent Study Theses. Paper 8563.
https://openworks.wooster.edu/independentstudy/8563
Disciplines
Other Computer Sciences | Other Mathematics
Keywords
machine learning, computer vision, object recognition, object detection, real-time, neural networks, TensorFlow, OpenCV, convolutional neural networks
Publication Date
2019
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2019 Bhargav Anandkumar Bhalodi