Automatic facial analysis for objective assessment of facial paralysis

Facial Paralysis is a condition causing decreased movement on one side of the face. A quantitative, objective and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents an approach based on the automatic analysis of patient video data. Facial feature localization and facial movement detection methods are discussed. An algorithm is presented to process the optical flow data to obtain the motion features in the relevant facial regions. Three classification methods are applied to provide quantitative evaluations of regional facial nerve function and the overall facial nerve function based on the House-Brackmann Scale. Experiments show the Radial Basis Function (RBF) Neural Network to have superior performance

Classification of Humans into Ayurvedic Prakruti Types using Computer Vision

Ayurveda, a 5000 years old Indian medical science, believes that the universe and hence humans are made up of five elements namely ether, fire, water, earth, and air. The three Doshas (Tridosha) Vata, Pitta, and Kapha originated from the combinations of these elements. Every person has a unique combination of Tridosha elements contributing to a person’s ‘Prakruti’. Prakruti governs the physiological and psychological tendencies in all living beings as well as the way they interact with the environment. This balance influences their physiological features like the texture and colour of skin, hair, eyes, length of fingers, the shape of the palm, body frame, strength of digestion and many more as well as the psychological features like their nature (introverted, extroverted, calm, excitable, intense, laidback), and their reaction to stress and diseases. All these features are coded in the constituents at the time of a person’s creation and do not change throughout their lifetime. Ayurvedic doctors analyze the Prakruti of a person either by assessing the physical features manually and/or by examining the nature of their heartbeat (pulse). Based on this analysis, they diagnose, prevent and cure the disease in patients by prescribing precision medicine. This project focuses on identifying Prakruti of a person by analysing his facial features like hair, eyes, nose, lips and skin colour using facial recognition techniques in computer vision. This is the first of its kind research in this problem area that attempts to bring image processing into the domain of Ayurveda

A theoretical eye model for uncalibrated real-time eye gaze estimation

Computer vision systems that monitor human activity can be utilized for many diverse applications. Some general applications stemming from such activity monitoring are surveillance, human-computer interfaces, aids for the handicapped, and virtual reality environments. For most of these applications, a non-intrusive system is desirable, either for reasons of covertness or comfort. Also desirable is generality across users, especially for humancomputer interfaces and surveillance. This thesis presents a method of gaze estimation that, without calibration, determines a relatively unconstrained user’s overall horizontal eye gaze. Utilizing anthropometric data and physiological models, a simple, yet general eye model is presented. The equations that describe the gaze angle of the eye in this model are presented. The procedure for choosing the proper features for gaze estimation is detailed and the algorithms utilized to find these points are described. Results from manual and automatic feature extraction are presented and analyzed. The error observed from this model is around 3± and the error observed from the implementation is around 6±. This amount of error is comparable to previous eye gaze estimation algorithms and it validates this model. The results presented across a set of subjects display consistency, which proves the generality of this model. A real-time implementation that operates around 17 frames per second displays the efficiency of the algorithms implemented. While there are many interesting directions for future work, the goals of this thesis were achieved