Ling Shao

TL;DR: A comprehensive review of recent Kinect-based computer vision algorithms and applications covering topics including preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping.

TL;DR: A simple but powerful color attenuation prior for haze removal from a single input hazy image is proposed and outperforms state-of-the-art haze removal algorithms in terms of both efficiency and the dehazing effect.

TL;DR: A comprehensive survey of different systems for fall detection and their underlying algorithms is given, divided into three main categories: wearable device based, ambience device based and vision based.

TL;DR: A powerful AGW baseline is designed, achieving state-of-the-art or at least comparable performance on twelve datasets for four different Re-ID tasks, and a new evaluation metric (mINP) is introduced, indicating the cost for finding all the correct matches, which provides an additional criteria to evaluate the Re- ID system for real applications.

TL;DR: This paper surveys state-of-the-art transfer learning algorithms in visual categorization applications, such as object recognition, image classification, and human action recognition, to find out if they can be efficiently solved.