Gesture Recognition from Data Streams of Human Motion Sensor Using Accelerated PSO Swarm Search Feature Selection Algorithm
المؤلفون المشاركون
Mohammed, Sabah
Fister, Iztok
Liang, Justin
Fister, Iztok
Fong, Simon
المصدر
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-03-30
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Human motion sensing technology gains tremendous popularity nowadays with practical applications such as video surveillance for security, hand signing, and smart-home and gaming.
These applications capture human motions in real-time from video sensors, the data patterns are nonstationary and ever changing.
While the hardware technology of such motion sensing devices as well as their data collection process become relatively mature, the computational challenge lies in the real-time analysis of these live feeds.
In this paper we argue that traditional data mining methods run short of accurately analyzing the human activity patterns from the sensor data stream.
The shortcoming is due to the algorithmic design which is not adaptive to the dynamic changes in the dynamic gesture motions.
The successor of these algorithms which is known as data stream mining is evaluated versus traditional data mining, through a case of gesture recognition over motion data by using Microsoft Kinect sensors.
Three different subjects were asked to read three comic strips and to tell the stories in front of the sensor.
The data stream contains coordinates of articulation points and various positions of the parts of the human body corresponding to the actions that the user performs.
In particular, a novel technique of feature selection using swarm search and accelerated PSO is proposed for enabling fast preprocessing for inducing an improved classification model in real-time.
Superior result is shown in the experiment that runs on this empirical data stream.
The contribution of this paper is on a comparative study between using traditional and data stream mining algorithms and incorporation of the novel improved feature selection technique with a scenario where different gesture patterns are to be recognized from streaming sensor data.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Fong, Simon& Liang, Justin& Fister, Iztok& Fister, Iztok& Mohammed, Sabah. 2015. Gesture Recognition from Data Streams of Human Motion Sensor Using Accelerated PSO Swarm Search Feature Selection Algorithm. Journal of Sensors،Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1070076
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Fong, Simon…[et al.]. Gesture Recognition from Data Streams of Human Motion Sensor Using Accelerated PSO Swarm Search Feature Selection Algorithm. Journal of Sensors No. 2015 (2015), pp.1-16.
https://search.emarefa.net/detail/BIM-1070076
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Fong, Simon& Liang, Justin& Fister, Iztok& Fister, Iztok& Mohammed, Sabah. Gesture Recognition from Data Streams of Human Motion Sensor Using Accelerated PSO Swarm Search Feature Selection Algorithm. Journal of Sensors. 2015. Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1070076
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1070076
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر