Dr. Lu FANG's Vision and Imaging Group

 

fanglu@sz.tsinghua.edu.cn

 

 

I obtained my Ph.D. degree from the ECE department in the Hong Kong University of Science and Technology (HKUST) in 2011, and was a postdoctoral research fellow in HKUST and Singapore University of Technology and Design (SUTD) working with Prof. Oscar C. Au and Prof. Ngai-Man Cheung respectively from 08/2011 till 10/2012. I joined in University of Science and Technology of China (USTC) as an Associate Professor in 2012.  I am currently an Associate Professor in Tsinghua University.

I was a visiting scholar in Northwestern University with the host of Prof. Aggelos K. Katsaggelos in 2010. I was a visiting scholar in Microsoft Research Asia (MSRA) with the host of Prof. Feng Wu from 08/2013 till 04/2014, awarded by “Star Track for Young Faculties” fellowship. In Aug. 2014, I was awarded by “Humboldt Research Fellowship for Experienced Researchers”, for visiting Technical University of Munich (TUM) with the host of Prof. Eckehard Steinbach.

 

RESEARCH INTERESTS

Computational Photography and Visual Computing, including Gigapixel Imaging, Image Deblurring, Subpixel Rendering, and 3D Reconstruction, etc.

 

RESEARCH PROJECTS (Complete Publication List)

 

Multiscale Gigapixel Video: A Cross Resolution Image Matching andWarping Approach

International Conference on Computational Photography 2017

Project Page

We present a multi-scale camera array to capture and synthesize gigapixel videos in an efficient way. Our acquisition setup contains a reference camera with a short-focus lens to get a large field-of-view video and a number of unstructured long-focus cameras to capture local-view details.

 

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Camera

arXiv 2016

Project Page

We present a new markerless motion capture end-to-end system for moving targets in a wide space without extra constraints like fixed capture volume, using multiple autonomous flying cameras.

 

Monocular Long-term Target Following on UAVs

Computer Vision in Vehicle Technology (CVVT) workshop in IEEE CVPR 2016

We investigate the challenging long-term visual tracking problem and its implementation on Unmanned Aerial Vehicles (UAVs).

 

Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation

under review, IEEE Trans. on Image Processing

This paper proposes a convolutional neural network that can fuse high-level prior for semantic image segmentation.

 

Deep Learning for Surface Material Classification Using Haptic and Visual Information

IEEE Trans. on Multimedia, 2016

This paper deals with the surface material classification problem based on a Fully Convolutional Network (FCN), taking acceleration signal and a corresponding image of the surface texture as inputs.

 

Computation and Memory Efficient Image Segmentation

IEEE Trans. on CSVT, 2016

This paper addresses the segmentation problem under limited computation and memory resources. Given a segmentation algorithm, we propose a framework that can reduce its computation time and memory requirement simultaneously, while preserving its accuracy.

 

Magic Glasses: From 2D to 3D

IEEE Trans. on CSVT, 2016

This paper proposes a virtual 3D eyeglasses try on system driven by a 2D Internet image of a human face wearing with a pair of eyeglasses.

 

Estimation of Virtual View Synthesis Distortion in 3D Video

IEEE Trans. on Image Processing, 2016 & IEEE TIP 2014.

This paper proposes an analytical model to estimate the synthesized view quality in 3D video. The model relates errors in the depth images to the synthesis quality, taking into account texture image characteristics, texture image quality, the virtual view position, and the rendering process.

 

Stereo Matching with Optimal Local Adaptive Radiometric Compensation

IEEE Signal Processing Letter, 2014

We propose a radiometrically invariant stereo matching method by approximating the spatially varying Pixel Value Correspondence Function (PVCF) between a corresponding pixel pair as a locally consistent polynomial within an optimal local adaptive window.

 

Robust Blur Kernel Estimation for License Plate Images from Fast Moving Vehicles

IEEE Trans. on Image Processing, 2016

This paper proposes a sparse representation scheme to deal with the snapshot of over-speed vehicle captured by surveillance camera that is frequently blurred due to fast motion.

 

Deblurring Saturated Night Images with Function-form Kernel

IEEE Trans. on Image Processing, 2015

This paper deals with the deblurring of night images that suffer low contrast, heavy noise and saturated regions. The key idea is to deduce blur kernels from saturated regions via a novel kernel representation and advanced algorithms.

 

Separable Kernel for Image Deblurring

IEEE Computer Vision and Pattern Recognition (CVPR), 2014

This paper deals with the image deblurring problem in a completely new perspective by proposing separable kernel - trajectory, intensity and defocus, to represent the inherent properties of the camera and scene system.

 

Adaptive Multispectral Demosaicking Based on Frequency Domain Analysis of Spectral Correlation

under review, IEEE Trans. on Image Processing

This paper deals with multispectral demosaicking where each band is significantly undersampled due to the increment in the number of bands.

 

Multichannel Non-Local Means Fusion for Color Image Denoising

IEEE Trans. on CSVT, 2013

This paper proposes a multichannel nonlocal means fusion (MNLF) scheme based on the inherent strong interchannel correlation feature of color images.

Subpixel Rendering: From Font Rendering to Image Subsampling

IEEE Signal Processing Magazine, 2012

This paper introduces subpixel arrangement in color displays, how subpixel rendering works, and several practical subpixel rendering applications in font rendering and image subsampling.