This collaborative research project aims at developing a new class of dialog-based, home robotic healthcare assistants to facilitate a new level of in-home, real-time care to elderly and depressed patients, providing lower total costs and higher quality of life. An emotive, physical avatar called companionbot that possesses the ability to engage humans in a way that is unobstructive and suspends disbelief will be built in this project.
This project aims at to develop and utilize humanoid robots for analyzing behavior principles of children with ASDs and go beyond simple goals of using robots as a neat toy to make kids smile or maybe even engage in joint attention.
The earthquake and tsunami that devastated parts of Japan is a terrible reminder of the power and danger of natural disasters. While we respectfully mourn the tragic loss of life and the hardships that the living are experiencing and will continue to experience for months and years to come, there are many opportunities to learn, to contribute, and to improve on current response methods.
In this research project, our focus is on developing automated computer vision techniques for measuring/recognizing spontaneous facial expressions and FACS action units and map onto expert human coding. We apply developed automated techniques to analyze emotion expressions of children with autism.
The focus of this research is to develop a novel holistic-based framework to estimate gaze direction. The gaze direction of an infant in a face-to-face interaction is classified as either 1) looking at the parent’s face or 2) looking away from the parent’s face.
Facial feature extraction is an important step in face recognition and is defined as the process of locating specific regions, points, landmarks, or curves/contours in a given 2-D image or a 3-D range image.
Most of the approaches that have been developed for 3-D face recognition are based on 3-D surface matching. I presented an approach for 3-D face recognition based on Ridge lines extracted from range facial images.
Graph Cut Optimization and Its Application in Image Blending
In the area of computer vision, optimization is an important issue. One of the new developed techniques that caught my attention recently is “Graph-Cut”. I worked on using this new optimization technique in applications such as image blending or image segmentation.
Video stabilization removes unwanted motion from video sequences, often caused by vibrations or other instabilities. This improves video viewability and can aid in detection and tracking in computer vision algorithms.
TeleMonitoring System for Patients with Total Knee Replacement
The subject of this project is to design and implement a home monitoring system for patients with knee rehabilitation recovering after surgery. Usually they go to hospital for exercising and they are monitored by physicians to assure that their knee performs enough degree of flexion (i.e., they can bend their knee and improve it over the exercise course).
Telemonintoring System for Patients with Congestive Heart Failure
Remote chronic illness management is a growing need in Colorado as the general population ages. Through the Urban Health Initiative, a team of researchers at the University of Denver and the Denver Health Medical Center are launching a pilot study focused on Congestive Heart Failure which is the second largest chronic illness in the U.S. The goal of this investigation is to reduce hospitalization by 25% through the use of a home monitoring system.