A facial recognition system is a computer application for automatically identifying or verifying person from digital image video frame source. One of the way to do this by comparing selected features and database.It typically used in security systems can be compared other biometrics such as fingerprint eye iris systems. In paper we focus on 3-D biometric recognision system. We critics giving effectiveness weaknesses. This also introduces scope India.

Recently consumer electronics products for the human device or machine interaction in smart healthcare systems have been widespread due to progress health monitoring hardware and remote diagnostic services. Affect recognition through thermal facial signatures is significant real-time human–machine (HMI) studies. The distribution of skin temperature displays explicit characteristics related affect arousal. When interacts with a computer, it challenging detect face track regions interest...

This paper presents a non-contact system based on twin channels of thermal and visual image sequences to register the affective states an individual during Human-Computer Interaction (HCI). The negative such as stress, anxiety, depression in students have raised significant concerns. necessitates smart HCI assisting tool for psychologists. In this paper, we propose two-stage classifying state by clustering emotional states. first stage obtains dominant ensemble cues from facial images using...

In this paper, we introduce an online facial expression recognition (FER) model, which infers the emotional states in real time. This model enables computer to interact more intelligently with user. Our proposed mechanism identifies frontal face along region of interest (ROI), extracts discriminating features from suitable landmarks, and classifies expressions. Histogram oriented gradient (HOG) is implemented extract landmark positions active regions, enhances system performance against all...

The status of mental health and mood human beings are well comprehensible by careful observation movements different body parts. Eye being the most prominent part, analysis eye parameters such as blink, gaze, opening closing rate provides important clues on conditions. present work can be viewed from a statistical machine learning perspective that utilizes blink information to study person. By using appropriate image processing techniques blinks subjects were collected through an...

This paper presents an architecture for estimating the posterior probabilities of disorders in affective health by clustering sequences emotional states. The considered are depression, anxiety, and stress, based on well-known DASS-21 model. visual thermal face image elicit states through a proposed cascaded Convolutional Neural Network (CCNN) framework CCNN has 16 layers containing convolutional, pooling, fully connected. same been used to independently train images determine every seven...

Breath is vital for survival and plays an essential role in enhancing the physical, mental, spiritual well-being of a human. Real-time breath pattern monitoring during Human-Computer Interaction (HCI) help diagnosis potential avoidance various health problems. However, state-of-the-art approaches are usually contacted basis and/or limited to medical facilities. In this paper, goal study investigate non-contact measurement technique pattern, framework has proposed recognizing shortness...

Objective The increasing rate of depression among university students is a cause great concern worldwide. With the recent growth in computer vision technology, eye movement features are proving beneficial assessment owing to their non-invasiveness. Our objective was determine presence through emotional elicitation by studying blink patterns student population.Method data 50 (26 males, 24 females) from different regions country within age group 21–26 years were collected using an experimental...

The integration of Information and Communications Technology (ICT) for mental Health (m-Health) detection control in the smart framework (e-Framework) opens opportunity developing intelligent Human-device Interaction (HDI) system. m-Health using multi-modality cues: Respiration Wave Pattern (RWP), Heart (HWP), visual RGB facial expression a person convey more accurate information to build robust efficient system an early stage recognition. This study proposes k-nearest neighbor (k-NN) based...