Chengjun Liu, Ph.D.
Department of Computer Science
New Jersey Institute of Technology
Ph.D., George Mason University
Professor Chengjun Liu’s research interests are in Computer Vision (Face/Iris Detection and Recognition, Video Processing), Machine Learning (Statistical Learning, Kernel Methods, Similarity Measures), Security (Biometrics), Pattern Recognition, and Image Processing.
A new technology that can verify a person´s identity using facial images is the goal of research by Chengjun Liu. He has developed a face recognition system that improves on previous technology by taking into account such factors as lighting and facial expressions. The system has tested 100 percent effective in matching videotaped images to those stored in government databases by comparing 62 features or facial landmarks. Liu recently received funding from the Department of Defense to support his research as part of the government´s effort for combating terrorism using face recognition technologies.
Click on the links below to read more about each research project. To view a full list of publications, click here
- Scene image classification using a wigner-based Local Binary Patterns descriptor
- Clustering-based Discriminant Analysis for Eye Detection
- New color GPHOG descriptors for object and scene image classification
- Discriminant analysis and similarity measure
- HaarHOG: Improving the HOG Descriptor for Image Classification
- New image descriptors based on color, texture, shape, and wavelets for object and scene image classification
- Effective use of color information for large scale face verification
- A New Bag of Words LBP (BoWL) Descriptor for Scene Image Classification
- Novel color gabor-lbp-phog (glp) descriptors for object and scene image classification
- Novel color HWML descriptors for scene and object image classification