A Multi-class Hand Gesture Recognition in Complex Background using Sequential Minimal Optimization

被引：0

作者：

Sheenu ^{[1
]}

Joshi, Garima ^{[1
]}

Vig, Renu ^{[1
]}

机构：

[1] Panjab Univ, UIET, ECE Dept, Chandigarh, India

来源：

2015 INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMPUTING AND CONTROL (ISPCC) | 2015年

关键词：

hand gesture; complex background; Jochentriesch; histograms of orientation gradient; sequential minimal optimization; SYSTEM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

this paper presents a novel approach for hand gesture recognition in complex background images. The method is based on Histograms of Orientation Gradient (HOG) which in independent of segmentation task followed by Sequential minimal Optimization (SMO). In our experiment we use benchmark Jochen-Triesch database for hand gesture recognition under complex and clutter background. In addition to this perturbation is added to images to increase the database. The vector size is reduced by increasing the number of pixels per cell without compromising accuracy. The proposed system gives overall recognition rate of 93.12% which demonstrates the robustness of the system under illumination changes, rotation and translation.

引用

页码：92 / 96

页数：5

共 50 条

[21] Hand number gesture recognition using recognized hand parts in depth images [J].

Dinh, Dong-Luong ;

Lee, Sungyoung ;

Kim, Tae-Seong .

MULTIMEDIA TOOLS AND APPLICATIONS, 2016, 75 (02) :1333-1348

[22] A Novel Approach to Hand Gesture Recognition for Virtual System Based on Adaptive Background Model [J].

Tan, Wenjun ;

Wu, Chengdong ;

Zhao, Shuying ;

Xie, Hualong .

E-ENGINEERING & DIGITAL ENTERPRISE TECHNOLOGY VII, PTS 1 AND 2, 2009, 16-19 :891-895

[23] Implementing Hand Gesture Recognition Using EMG on the Zynq Circuit [J].

Kerdjidj, O. ;

Amara, K. ;

Harizi, F. ;

Boumridja, H. .

IEEE SENSORS JOURNAL, 2023, 23 (09) :10054-10061

[24] HAND GESTURE RECOGNITION AND MOTION ESTIMATION USING THE KINECT SENSOR [J].

Wang, Bin ;

Li, Yunze ;

Lang, Haoxiang ;

Wang, Ying .

MECHATRONIC SYSTEMS AND CONTROL, 2020, 48 (01) :17-24

[25] Modeling and recognition of hand gesture using colored Petri nets [J].

Nam, Y ;

Wohn, K ;

Lee-Kwang, H .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 1999, 29 (05) :514-521

[26] Hand Gesture Detection and Recognition Using Principal Component Analysis [J].

Dardas, Nasser H. ;

Petriu, Emil M. .

2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS (CIMSA), 2011, :11-16

[27] Hand Gesture Recognition Using Movidius Neural Compute Stick [J].

Ab Hamid, Muhammad Fawwaz ;

Zaman, Fadhlan Hafizhelmi Kamaru .

2019 IEEE 9TH INTERNATIONAL CONFERENCE ON SYSTEM ENGINEERING AND TECHNOLOGY (ICSET), 2019, :510-514

[28] Hand Region Extraction and Gesture Recognition using entropy analysis [J].

Shin, Jae-Ho ;

Lee, Jong-Shill ;

Kil, Se-Kee ;

Shen, Dong-Fan ;

Ryu, Je-Goon ;

Lee, Eung-Hyuk ;

Min, Hong-Ki ;

Hong, Seung-Hong .

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2006, 6 (2A) :216-222

[29] Real time Hand Gesture Recognition using AVR Microcontroller [J].

Shakunthaladevi, M. ;

Revathi, R. B. .

2014 INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND EMBEDDED SYSTEMS (ICICES), 2014,

[30] EMG based Hand Gesture Recognition using Deep Learning [J].

Ozdemir, Mehmet Akif ;

Kisa, Deniz Hande ;

Guren, Onan ;

Onan, Aytug ;

Akan, Aydin .

2020 MEDICAL TECHNOLOGIES CONGRESS (TIPTEKNO), 2020,

← 1 2 3 4 5 →