Posture Recognition Using Correlation Filter Classifier
نویسندگان
چکیده
In this paper, we described an innovative methodology of recognizing four main postures namely standing, sitting, bending and lying position using correlation filter particularly Unconstrained Minimum Average Correlation Energy (UMACE). Initial results prove the UMACE filters offer significant potential in posture recognition task. The filter was subjected to a challenging task to recognize human posture without any restriction on the gender, clothing and posture variations. Classification outcome confirm the UMACE filter performs remarkably well with an average accuracy of 85%.
منابع مشابه
The Enhancement of Low-level Classifications in Sequential Syntactic High-level Classifiers
This paper surveys a new research field of object behavior classification using sequential syntactic pattern recognition, which recognizes high-level object behaviors while in parallel recovering from low-level object recognition classification errors. A new approach of syntactical object behavior classification with a robust implementation is introduced. It is an innovative approach that requi...
متن کاملTrends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery
In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filte...
متن کاملThai Finger-Spelling Recognition Using a Cascaded Classifier Based on Histogram of Orientation Gradient Features
Hand posture recognition is an essential module in applications such as human-computer interaction (HCI), games, and sign language systems, in which performance and robustness are the primary requirements. In this paper, we proposed automatic classification to recognize 21 hand postures that represent letters in Thai finger-spelling based on Histogram of Orientation Gradient (HOG) feature (whic...
متن کاملFeature Selection Based on Mutual Correlation
Feature selection is a critical procedure in many pattern recognition applications. There are two distinct mechanisms for feature selection namely the wrapper methods and the filter methods. The filter methods are generally considered inferior to wrapper methods, however wrapper methods are computationally more demanding than filter methods. A novel filter feature selection method based on mutu...
متن کاملSemi-supervised Learning for Adaptation of Human Activity Recognition Classifier to the User
The success of many ambient intelligence applications depends on accurate prediction of human activities. Since posture and movement characteristics are unique for each individual person, the adaptation of activity recognition is essential. This paper presents a method for on-line adaptation of activity recognition using semi-supervised learning. The method uses a generic classifier trained on ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008