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Motion recognition with smart phone embedded 3-axis accelerometer sensor
As the technology surrounding smart phone devices has changed over the past few years, we now find a device containing a collection of sensors. Indeed, one can say that the development of smart phones has been one of the most important advances in science and technology. We will show an additional u...
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creator | Hyunju Cho Sangchul Kim Jinsuk Baek Fisher, P. S. |
description | As the technology surrounding smart phone devices has changed over the past few years, we now find a device containing a collection of sensors. Indeed, one can say that the development of smart phones has been one of the most important advances in science and technology. We will show an additional usage for the smart phone: utilizing it for a generic, hardware, gaming controller. We will show how a motion recognition mechanism can be used for determining rate of change and position of the phone as it moves in 3D-space using the embedded 3-axes accelerometer sensor. Upon sensing a user's motions with the smart phone, the corresponding accelerometer values are transmitted to the gaming console through the Wi-Fi communication. Motion recognition is then performed at the gaming console using a pattern matching mechanism. The proposed mechanism is applied to the game of tennis to recognize three primary ground stroke motions: the forehand stroke, backhand stroke, and service. With individual calibration for these three motions, we show how accurately the system can recognize the motions, and derive ball-hit likelihood. These types of results, when fully realized, can provide a much richer and simpler experience for the user. |
doi_str_mv | 10.1109/ICSMC.2012.6377845 |
format | conference_proceeding |
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The proposed mechanism is applied to the game of tennis to recognize three primary ground stroke motions: the forehand stroke, backhand stroke, and service. With individual calibration for these three motions, we show how accurately the system can recognize the motions, and derive ball-hit likelihood. 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Motion recognition is then performed at the gaming console using a pattern matching mechanism. The proposed mechanism is applied to the game of tennis to recognize three primary ground stroke motions: the forehand stroke, backhand stroke, and service. With individual calibration for these three motions, we show how accurately the system can recognize the motions, and derive ball-hit likelihood. These types of results, when fully realized, can provide a much richer and simpler experience for the user.</description><subject>Acceleration</subject><subject>Accelerometers</subject><subject>acceleromter</subject><subject>augmented reality</subject><subject>Games</subject><subject>Gravity</subject><subject>motion recognition</subject><subject>Pattern matching</subject><subject>smart phone</subject><subject>Smart phones</subject><subject>Vectors</subject><issn>1062-922X</issn><issn>2577-1655</issn><isbn>9781467317139</isbn><isbn>1467317136</isbn><isbn>1467317144</isbn><isbn>9781467317122</isbn><isbn>9781467317146</isbn><isbn>1467317128</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kNtKAzEYhOMJ3Na-gN7kBbbmz3FzKYvaQosXKnhXssm_NtLdlM2C-vYWrVczMB_DMIRcA5sDMHu7rJ_X9Zwz4HMtjKmkOiETkNoIMCDlKSm4MqYErdQZmVlT_WfCnpMCmOal5fztkkxy_mCMMwlVQRbrNMbU0wF9eu_jr_-M45bmzg0j3W9TjxS7BkPAQEXpvmKmznvc4ZA6HHGgGfuchity0bpdxtlRp-T14f6lXpSrp8dlfbcqIxg1ltZLJ02FXgKXrtFWBATHrAAMDRet5-CcCN4LNMICC545rpEdSGNapcWU3Pz1RkTc7Id42Pm9OT4ifgDxLVFz</recordid><startdate>201210</startdate><enddate>201210</enddate><creator>Hyunju Cho</creator><creator>Sangchul Kim</creator><creator>Jinsuk Baek</creator><creator>Fisher, P. S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201210</creationdate><title>Motion recognition with smart phone embedded 3-axis accelerometer sensor</title><author>Hyunju Cho ; Sangchul Kim ; Jinsuk Baek ; Fisher, P. S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-9c4a478ec4124ab693de1a0931edb23fc21aa3dcc3e73910dc0a26e0b6977f563</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Acceleration</topic><topic>Accelerometers</topic><topic>acceleromter</topic><topic>augmented reality</topic><topic>Games</topic><topic>Gravity</topic><topic>motion recognition</topic><topic>Pattern matching</topic><topic>smart phone</topic><topic>Smart phones</topic><topic>Vectors</topic><toplevel>online_resources</toplevel><creatorcontrib>Hyunju Cho</creatorcontrib><creatorcontrib>Sangchul Kim</creatorcontrib><creatorcontrib>Jinsuk Baek</creatorcontrib><creatorcontrib>Fisher, P. S.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hyunju Cho</au><au>Sangchul Kim</au><au>Jinsuk Baek</au><au>Fisher, P. S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Motion recognition with smart phone embedded 3-axis accelerometer sensor</atitle><btitle>2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)</btitle><stitle>ICSMC</stitle><date>2012-10</date><risdate>2012</risdate><spage>919</spage><epage>924</epage><pages>919-924</pages><issn>1062-922X</issn><eissn>2577-1655</eissn><isbn>9781467317139</isbn><isbn>1467317136</isbn><eisbn>1467317144</eisbn><eisbn>9781467317122</eisbn><eisbn>9781467317146</eisbn><eisbn>1467317128</eisbn><abstract>As the technology surrounding smart phone devices has changed over the past few years, we now find a device containing a collection of sensors. Indeed, one can say that the development of smart phones has been one of the most important advances in science and technology. We will show an additional usage for the smart phone: utilizing it for a generic, hardware, gaming controller. We will show how a motion recognition mechanism can be used for determining rate of change and position of the phone as it moves in 3D-space using the embedded 3-axes accelerometer sensor. Upon sensing a user's motions with the smart phone, the corresponding accelerometer values are transmitted to the gaming console through the Wi-Fi communication. Motion recognition is then performed at the gaming console using a pattern matching mechanism. The proposed mechanism is applied to the game of tennis to recognize three primary ground stroke motions: the forehand stroke, backhand stroke, and service. With individual calibration for these three motions, we show how accurately the system can recognize the motions, and derive ball-hit likelihood. These types of results, when fully realized, can provide a much richer and simpler experience for the user.</abstract><pub>IEEE</pub><doi>10.1109/ICSMC.2012.6377845</doi><tpages>6</tpages></addata></record> |
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source | IEEE Xplore All Conference Series |
subjects | Acceleration Accelerometers acceleromter augmented reality Games Gravity motion recognition Pattern matching smart phone Smart phones Vectors |
title | Motion recognition with smart phone embedded 3-axis accelerometer sensor |
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