Loading…
Application of a neural network in recognizing facial expression
Input to the neural network program consists of facial images from a video source. The program uses the back propagation algorithm to train the network and to classify input data based on the subject's posed facial expression. Training and testing were performed with multiple individuals. The n...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference Proceeding |
| Language: | English |
| Subjects: | |
| Online Access: | Request full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | |
| container_end_page | 207 |
| container_issue | |
| container_start_page | 206 |
| container_title | |
| container_volume | |
| creator | Donohue, B.A. Bronzino, J.D. DiLiberti, J.H. Olson, D.P. Schweitzer, L.R. Walsh, P. |
| description | Input to the neural network program consists of facial images from a video source. The program uses the back propagation algorithm to train the network and to classify input data based on the subject's posed facial expression. Training and testing were performed with multiple individuals. The network was trained on a set consisting of 34 happy and 34 sad images from five different subjects. Additionally, the network was tested with images of subjects which were not included in training. In this case, training was performed using 24 happy and 24 sad images of three subjects. Testing was performed using ten happy and ten sad images of two new subjects. In preliminary testing, the network responded correctly for 85% of the 20 test cases. The ability of the network to generalize this discrimination successfully to new individuals is also demonstrated.< > |
| doi_str_mv | 10.1109/NEBC.1991.154648 |
| format | conference_proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_154648</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>154648</ieee_id><sourcerecordid>154648</sourcerecordid><originalsourceid>FETCH-LOGICAL-i172t-d2a84aa89726f50088d4676712b436a266c94ca2a69c04186b632de12883f7c73</originalsourceid><addsrcrecordid>eNotj01LxDAYhAMiKGvv4il_oDVvkubj5lrWD1j0oufl3TRZorUtScWPX29gHR6YwzADQ8glsAaA2eunzW3XgLXQQCuVNCekstqwgmAFe0aqnN9YkWyZFu05uVnP8xAdLnEa6RQo0tF_JhyKLV9TeqdxpMm76TDG3zgeaEAXS-q_5-RzLqULchpwyL769xV5vdu8dA_19vn-sVtv6wiaL3XP0UhEYzVXoWXMmF4qrTTwvRQKuVLOSocclXVMglF7JXjvgRsjgnZarMjVcTd673dzih-YfnbHm-IP4yVHCQ</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Application of a neural network in recognizing facial expression</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Donohue, B.A. ; Bronzino, J.D. ; DiLiberti, J.H. ; Olson, D.P. ; Schweitzer, L.R. ; Walsh, P.</creator><creatorcontrib>Donohue, B.A. ; Bronzino, J.D. ; DiLiberti, J.H. ; Olson, D.P. ; Schweitzer, L.R. ; Walsh, P.</creatorcontrib><description>Input to the neural network program consists of facial images from a video source. The program uses the back propagation algorithm to train the network and to classify input data based on the subject's posed facial expression. Training and testing were performed with multiple individuals. The network was trained on a set consisting of 34 happy and 34 sad images from five different subjects. Additionally, the network was tested with images of subjects which were not included in training. In this case, training was performed using 24 happy and 24 sad images of three subjects. Testing was performed using ten happy and ten sad images of two new subjects. In preliminary testing, the network responded correctly for 85% of the 20 test cases. The ability of the network to generalize this discrimination successfully to new individuals is also demonstrated.< ></description><identifier>ISBN: 9780780300309</identifier><identifier>ISBN: 0780300300</identifier><identifier>DOI: 10.1109/NEBC.1991.154648</identifier><language>eng</language><publisher>IEEE</publisher><subject>Biomedical engineering ; Biomedical imaging ; Computed tomography ; Face recognition ; Hospitals ; Humans ; Intelligent networks ; Neural networks ; Pattern recognition ; Time of arrival estimation</subject><ispartof>Proceedings of the 1991 IEEE Seventeenth Annual Northeast Bioengineering Conference, 1991, p.206-207</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/154648$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/154648$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Donohue, B.A.</creatorcontrib><creatorcontrib>Bronzino, J.D.</creatorcontrib><creatorcontrib>DiLiberti, J.H.</creatorcontrib><creatorcontrib>Olson, D.P.</creatorcontrib><creatorcontrib>Schweitzer, L.R.</creatorcontrib><creatorcontrib>Walsh, P.</creatorcontrib><title>Application of a neural network in recognizing facial expression</title><title>Proceedings of the 1991 IEEE Seventeenth Annual Northeast Bioengineering Conference</title><addtitle>NEBC</addtitle><description>Input to the neural network program consists of facial images from a video source. The program uses the back propagation algorithm to train the network and to classify input data based on the subject's posed facial expression. Training and testing were performed with multiple individuals. The network was trained on a set consisting of 34 happy and 34 sad images from five different subjects. Additionally, the network was tested with images of subjects which were not included in training. In this case, training was performed using 24 happy and 24 sad images of three subjects. Testing was performed using ten happy and ten sad images of two new subjects. In preliminary testing, the network responded correctly for 85% of the 20 test cases. The ability of the network to generalize this discrimination successfully to new individuals is also demonstrated.< ></description><subject>Biomedical engineering</subject><subject>Biomedical imaging</subject><subject>Computed tomography</subject><subject>Face recognition</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Intelligent networks</subject><subject>Neural networks</subject><subject>Pattern recognition</subject><subject>Time of arrival estimation</subject><isbn>9780780300309</isbn><isbn>0780300300</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1991</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj01LxDAYhAMiKGvv4il_oDVvkubj5lrWD1j0oufl3TRZorUtScWPX29gHR6YwzADQ8glsAaA2eunzW3XgLXQQCuVNCekstqwgmAFe0aqnN9YkWyZFu05uVnP8xAdLnEa6RQo0tF_JhyKLV9TeqdxpMm76TDG3zgeaEAXS-q_5-RzLqULchpwyL769xV5vdu8dA_19vn-sVtv6wiaL3XP0UhEYzVXoWXMmF4qrTTwvRQKuVLOSocclXVMglF7JXjvgRsjgnZarMjVcTd673dzih-YfnbHm-IP4yVHCQ</recordid><startdate>1991</startdate><enddate>1991</enddate><creator>Donohue, B.A.</creator><creator>Bronzino, J.D.</creator><creator>DiLiberti, J.H.</creator><creator>Olson, D.P.</creator><creator>Schweitzer, L.R.</creator><creator>Walsh, P.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1991</creationdate><title>Application of a neural network in recognizing facial expression</title><author>Donohue, B.A. ; Bronzino, J.D. ; DiLiberti, J.H. ; Olson, D.P. ; Schweitzer, L.R. ; Walsh, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i172t-d2a84aa89726f50088d4676712b436a266c94ca2a69c04186b632de12883f7c73</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1991</creationdate><topic>Biomedical engineering</topic><topic>Biomedical imaging</topic><topic>Computed tomography</topic><topic>Face recognition</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Intelligent networks</topic><topic>Neural networks</topic><topic>Pattern recognition</topic><topic>Time of arrival estimation</topic><toplevel>online_resources</toplevel><creatorcontrib>Donohue, B.A.</creatorcontrib><creatorcontrib>Bronzino, J.D.</creatorcontrib><creatorcontrib>DiLiberti, J.H.</creatorcontrib><creatorcontrib>Olson, D.P.</creatorcontrib><creatorcontrib>Schweitzer, L.R.</creatorcontrib><creatorcontrib>Walsh, P.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Donohue, B.A.</au><au>Bronzino, J.D.</au><au>DiLiberti, J.H.</au><au>Olson, D.P.</au><au>Schweitzer, L.R.</au><au>Walsh, P.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Application of a neural network in recognizing facial expression</atitle><btitle>Proceedings of the 1991 IEEE Seventeenth Annual Northeast Bioengineering Conference</btitle><stitle>NEBC</stitle><date>1991</date><risdate>1991</risdate><spage>206</spage><epage>207</epage><pages>206-207</pages><isbn>9780780300309</isbn><isbn>0780300300</isbn><abstract>Input to the neural network program consists of facial images from a video source. The program uses the back propagation algorithm to train the network and to classify input data based on the subject's posed facial expression. Training and testing were performed with multiple individuals. The network was trained on a set consisting of 34 happy and 34 sad images from five different subjects. Additionally, the network was tested with images of subjects which were not included in training. In this case, training was performed using 24 happy and 24 sad images of three subjects. Testing was performed using ten happy and ten sad images of two new subjects. In preliminary testing, the network responded correctly for 85% of the 20 test cases. The ability of the network to generalize this discrimination successfully to new individuals is also demonstrated.< ></abstract><pub>IEEE</pub><doi>10.1109/NEBC.1991.154648</doi><tpages>2</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISBN: 9780780300309 |
| ispartof | Proceedings of the 1991 IEEE Seventeenth Annual Northeast Bioengineering Conference, 1991, p.206-207 |
| issn | |
| language | eng |
| recordid | cdi_ieee_primary_154648 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biomedical engineering Biomedical imaging Computed tomography Face recognition Hospitals Humans Intelligent networks Neural networks Pattern recognition Time of arrival estimation |
| title | Application of a neural network in recognizing facial expression |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T11%3A37%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Application%20of%20a%20neural%20network%20in%20recognizing%20facial%20expression&rft.btitle=Proceedings%20of%20the%201991%20IEEE%20Seventeenth%20Annual%20Northeast%20Bioengineering%20Conference&rft.au=Donohue,%20B.A.&rft.date=1991&rft.spage=206&rft.epage=207&rft.pages=206-207&rft.isbn=9780780300309&rft.isbn_list=0780300300&rft_id=info:doi/10.1109/NEBC.1991.154648&rft_dat=%3Cieee_6IE%3E154648%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i172t-d2a84aa89726f50088d4676712b436a266c94ca2a69c04186b632de12883f7c73%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=154648&rfr_iscdi=true |