Source Themes

In this paper, we address the issue of video camera vibration and jittering by developing an effective approach to traffic flow monitoring under daytime conditions using the machine learning and computer vision techniques to extract motion traffic data parameters from the videos captured by the static surveillance camera installed and fixed at the intersection.

In this study, we propose a novel CLAHE-based nighttime image contrast enhancement approach for vehicle detection under nighttime conditions, which improves the contrast of low-quality nighttime images while preventing over-enhancement by employing the image dehazing technique.

This paper introduces a new methodology aimed at comfort for the driver in-the-wild multimodal corpus creation for audio-visual speech recognition in driver monitoring systems.