Our research lab is focusing on developing intelligent video analytics (IVASs) algorithms for object detection, tracking, and abnormal detection, among various computer vision applications, particularly in the area of video surveillance. 

Given the limited model capacity with a finite training dataset, it is difficult to satisfy all domains using a single model in general AI process. To overcome these limitations, it is necessary to adapt the universal model to specific domains in the inference phase with real-time constraints.

Our research lab is conducting studies to quantify and predict users' Quality of Experience(QoE), considering hardware and content characteristics, in various multimedia environments such as 3D displays, AR, VR, and others.