An Evaluation Metric for Object Detection Algorithms in Autonomous Navigation Systems and its Application to a Real-Time Alerting System

Machiraju, Harshitha and Channappayya, Sumohana (2018) An Evaluation Metric for Object Detection Algorithms in Autonomous Navigation Systems and its Application to a Real-Time Alerting System. In: 25th IEEE International Conference on Image Processing (ICIP), 7-10 October 2018, Athens, Greece.

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Abstract

An autonomous navigation system relies on a number of sensors including radar, LIDAR and a visible light camera for its operation. We focus our attention on the visible light camera in this work. Object detection is the key first step to processing the video input from the camera. Specifically, we address the problem of assessing the performance of object detection algorithms in hazardous driving conditions that an autonomous navigation system is expected to encounter in a realistic scenario. To this end, we propose a novel metric for quantifying the degradation in performance of an object detection algorithm under different weather conditions. Additionally’ we introduce a real-time method to detect extreme variations in performance of the algorithm that can be used to issue an alert. We evaluate the performance of our metric and alerting system and demonstrate its utility using the YOLOv2 object detection algorithm trained on the KITTI and virtual KITTI dataset.

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IITH Creators:
IITH CreatorsORCiD
Channappayya, SumohanaUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Autonomous vehicles, Object detection, Object recognition, Extreme weather conditions
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 14 Sep 2018 04:40
Last Modified: 14 Sep 2018 04:40
URI: http://raiith.iith.ac.in/id/eprint/4436
Publisher URL: http://doi.org/10.1109/ICIP.2018.8451718
Related URLs:

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