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In recent years, video analysis using Artificial Intelligence (AI) has beenwidely used, due to the remarkable development of image recognition technologyusing deep learning. In 2019, the Moving Picture Experts Group (MPEG) hasstarted standardization of Video Coding for Machines (VCM) as a video codingtechnology for image recognition. In the framework of VCM, both higher imagerecognition accuracy and video compression performance are required. In thispaper, we propose an extention scheme of video coding for object detectionusing Versatile Video Coding (VVC). Unlike video for human vision, video usedfor object detection does not require a large image size or high contrast.Since downsampling of the image can reduce the amount of information to betransmitted. Due to the decrease in image contrast, entropy of the imagebecomes smaller. Therefore, in our proposed scheme, the original image isreduced in size and contrast, then coded with VVC encoder to achieve highcompression performance. Then, the output image from the VVC decoder isrestored to its original image size using the bicubic method. Experimentalresults show that the proposed video coding scheme achieves better codingperformance than regular VVC in terms of object detection accuracy.

VVC Extension Scheme for Object Detection Using Contrast Reduction