Open AccessObject Detection and Classification for Autonomous Vehicle
Author(s) -
Bulla Rajesh,
D. RamaKrishna,
A. Ramakrishna Raju,
Ameet Chavan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1817/1/012004
Subject(s) - toolbox , matlab , computer science , object detection , computer vision , artificial intelligence , tracking (education) , video tracking , track (disk drive) , detector , object (grammar) , image processing , work (physics) , real time computing , simulation , pattern recognition (psychology) , image (mathematics) , engineering , operating system , mechanical engineering , psychology , telecommunications , pedagogy , programming language
The proposed work presents efficient objection detection and tracking algorithm for autonomous vehicles, which is developed in MATLAB with Image Processing Computer Version Toolbox and Automated Driving Toolbox. The developed algorithm track and detects moving and stationary objects such as other vehicles, pedestrians, and traffic lanes. Accurate and efficient tracking are important to analyze object behavior. For this work various build in detectors from MATLAB tool box were tested and compared. The evaluation of algorithm was carried on for 19 short videos from 8 seconds to 23 seconds, and then it applied to K-dataset and full road experiments by the Automated Driving Lab. The full road tests are between one to five minutes, including CAR to CAR WEST, CAR WEST to CAR, and campus marked roads.