出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Nowadays, the need for research on an intelligent video monitoring system is increasing
worldwide. Among the object detection methods, the core technology of the intelligent video
monitoring system, or object detection using a deep learning-based convolutional neural network,
is used widely due to its proven performance. Nonetheless, deep learning-based object detection
requires many hardware resources because it decodes the videos to analyze. Therefore, this
article suggests an advanced object recognition technique by conducting compressed video
stream-based object detection in order to reduce consumption of resources for object detection as
well as improve performance and confirms via the performance evaluation that speed and
recognition rate improved compared to existing algorithms such as YOLO, SSD, and Faster RCNN.
