0508623 20240103222553.720190919235959.9 85071460372 10.1007/978-3-030-27202-9_36 8 s. P cav_un_epca*0508965978-3-030-27201-20302-9743397-404ChamSpringer2019KarrayFakhri CampilhoAurélioYuAlfred Lip movement detection Tongue segmentation Speech therapy cav_un_auth*0332672 Bílková Zuzana UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0283562 Novozámský Adam UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0370910 Dominec Adam UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0380013 Greško Šimon UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101238 Zitová Barbara UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0370909 Paroubková Markéta UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2019/ZOI/bilkova-0508623.pdf cav_un_auth*0369114 TJ01000181 GA TA ČR The presented paper proposes a new method for unique automatic evaluation of speech therapy exercises, one part of the future software system for speech therapy support. The method is based on the detection of the lips and tongue movements, which will help to evaluate the quality of the exercise implementation. Four different types of exercises are introduced and the corresponding features, capturing the quality of the movements, are shown. The method was tested using manually annotated data and the proposed features were evaluated and analyzed. At the second part, the tongue detection is proposed based on the convolutional neural network approach and preliminary results were shown. cav_un_auth*0380014 Image Analysis and Recognition. ICIAR 2019 /16./ 20190827 20190829 Waterloo CA JC 10000 10200 10201 2020 6 PR RVO:67985556 http://hdl.handle.net/11104/0299789 S 2019 85071460372 SCOPUS PUBMED WOS cav_un_epca*0508965 Image Analysis and Recognition : 16th International Conference, ICIAR 2019, Waterloo, ON, Canada, August 27–29, 2019 978-3-030-27201-2 0302-9743 397 404 Cham Springer 2019 Lecture Notes in Computer Science 11662 Karray Fakhri 340 340 Campilho Aurélio 340 Yu Alfred