RTScale: Sensitivity-Aware Adaptive Image Scaling for Real-Time Object Detection

Seonyeong Heo, Shinnung Jeong, Hanjun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Real-time object detection is crucial in autonomous driving. To avoid catastrophic accidents, an autonomous car should detect objects with multiple cameras and make decisions within a certain time limit. Object detection systems can meet the real-time constraint by dynamically downsampling input images to proper scales according to their time budget. However, simply applying the same scale to all the images from multiple cameras can cause unnecessary accuracy loss because downsampling can incur a significant accuracy loss for some images. To reduce the accuracy loss while meeting the real-time constraint, this work proposes RTScale, a new adaptive real-time image scaling scheme that applies different scales to different images reflecting their sensitivities to the scaling and time budget. RTScale infers the sensitivities of multiple images from multiple cameras and determines an appropriate image scale for each image considering the real-time constraint. This work evaluates object detection accuracy and latency with RTScale for two driving datasets. The evaluation results show that RTScale can meet real-time constraints with minimal accuracy loss.

Original languageEnglish
Title of host publication34th Euromicro Conference on Real-Time Systems, ECRTS 2022
EditorsMartina Maggio, Martina Maggio
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959772396
Publication statusPublished - 2022 Jul 1
Event34th Euromicro Conference on Real-Time Systems, ECRTS 2022 - Modena, Italy
Duration: 2022 Jul 52022 Jul 8

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
ISSN (Print)1868-8969


Conference34th Euromicro Conference on Real-Time Systems, ECRTS 2022

Bibliographical note

Publisher Copyright:
© Seonyeong Heo, Shinnung Jeong, and Hanjun Kim

All Science Journal Classification (ASJC) codes

  • Software


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