Guoying Zhao

TL;DR: A novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered and both the VLBP and LBP-TOP clearly outperformed the earlier approaches.

TL;DR: Experimental results on the Brodatz and KTH-TIPS2-a texture databases show that WLD impressively outperforms the other widely used descriptors (e.g., Gabor and SIFT), and experimental results on human face detection also show a promising performance comparable to the best known results onThe MIT+CMU frontal face test set, the AR face data set, and the CMU profile test set.

TL;DR: Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains and provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems.

TL;DR: An improved micro-expression recognition system, CASME II, is built, with higher temporal resolution (200 fps) and spatial resolution (about 280×340 pixels on facial area) and elicited participants' facial expressions in a well-controlled laboratory environment and proper illumination.

TL;DR: A novel research on a dynamic facial expression recognition, using near-infrared (NIR) video sequences and LBP-TOP feature descriptors and component-based facial features are presented to combine geometric and appearance information, providing an effective way for representing the facial expressions.