Human Recognition-Behavioral Adaptation System

HMM Adaptation for Improving a Human Activity Recognition System

Abstract: When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Recognition (HAR) system. This paper proposes a user adaptation technique for improving a HAR system based on Hidden Markov Models (HMMs). T...

Co-adaptation in a Handwriting Recognition System

Handwriting is a natural and versatile method for humancomputer interaction, especially on small mobile devices such as smart phones. However, as handwriting varies significantly from person to person, it is difficult to design handwriting recognizers that perform well for all users. A natural solution is to use machine learning to adapt the recognizer to the user. One complicating factor is th...

Assessment of the Behavioral Inhibition System and the Behavioral Approach System: Adaptation

Human Action Recognition System

uman action recognition has evoked considerable interest in the various research areas and applications due to its potential use in proactive computing. The objective of this work is to recognize various human actions like run, jump, walk etc. Moving Object detection and tracking is the first step for action recognition. The algorithm first makes use of the statistical background model and back...

Human Emotion Recognition System

This paper discusses the application of feature extraction of facial expressions with combination of neural network for the recognition of different facial emotions (happy, sad, angry, fear, surprised, neutral etc..). Humans are capable of producing thousands of facial actions during communication that vary in complexity, intensity, and meaning. This paper analyses the limitations with existing...