Um Modelo Computacional para Acessibilidade em Cidades Inteligentes
Resumo
Este artigo apresenta o MASC, que é um modelo computacional para acessibilidade em cidades inteligentes. A utilização da computação ubíqua na área da acessibilidade oportuniza soluções para suporte a pessoas com deficiências (PcDs). Diferente das abordagens propostas, o MASC utiliza as interações das PcDs para composição de trilhas que serão oferecidas como serviço. Além disso é genérico pois suporta diferentes tipos de deficiências e é indicado para aplicações massivas. Foi desenvolvido um protótipo para avaliar desempenho e funcionalidade. Esta avaliação foi realizada com dados gerados por um simulador de contextos em uma região localizada no centro da cidade São Leopoldo - RS. Os resultados apresentados nos testes indicam que os serviços oferecidos pelo modelo podem ser implantados nas cidades inteligentes para colaborar com acessibilidade, auxiliando PcDs, profissionais da saúde e administração pública.
Palavras-chave:
Acessibilidade ubíqua, cidade acessível, modelo para suporte, pessoas com deficiências
Referências
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A. Kale, A. Roychowdhury, and R. Chellappa. Fusion of gait and face for human identification. In Proc. of IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), volume 5, pages V–901–4, May 2004.
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G. Shakhnarovich and T. Darrell. On probabilistic combination of face and gait cues for identification. In Proc. of 5th IEEE Int. Conf. on Automatic Face and Gesture Recognition, pages 169–174, May 2002.
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R. Chellappa and G. Aggarwal. Advances in Biometrics: Sensors, Algorithms and Systems, chapter Pose and Illumination Issues in Face- and Gait- Based Identification, pages 307–322. Springer London, London, 2008.
G. Chetty and M. Singh. Information fusion for identity verification. World Academy of Science, Engineering and Technology, 5(5):979–984, 2011.
M. Eskandari, ¨ O. Toygar, and H. Demirel. Feature extractor selection for face–iris multimodal recognition. Signal, Image and Video Processing, 8(6):1189–1198, 2014.
M. Gavrilova, M. Monwar, and I. Global. Multimodal Biometrics and Intelligent Image Processing for Security Systems. IGI Global, 2013.
X. Geng, L. Wang, M. Li, Q. Wu, and K. Smith-Miles. Adaptive fusion of gait and face for human identification in video. In Proc. of IEEE Workshop on App. of Comp. Vision (WACV), pages 1–6, Jan. 2008.
Y. Guan, X. Wei, C.-T. Li, and Y. Keller. People identification and tracking through fusion of facial and gait features. In V. Cantoni, D. Dimov, and M. Tistarelli, editors, Biometric Authentication, pages 209–221. Springer, 2014.
Y. Guan, X. Wei, C.-T. Li, G. Marcialis, F. Roli, and M. Tistarelli. Combining gait and face for tackling the elapsed time challenges. In Proc. of IEEE 6th Int. Conf. on Biometrics: Theory, App. and Sys. (BTAS), pages 1–8, Sept 2013.
F. He, Y. Liu, X. Zhu, C. Huang, Y. Han, and Y. Chen. Score level fusion scheme based on adaptive local gabor features for face-iris-fingerprint multimodal biometric. J. of Electronic Imaging, 23(3):033019, 2014.
M. Hofmann, S. Schmidt, A. Rajagopalan, and G. Rigoll. Combined face and gait recognition using alpha matte preprocessing. In Proc. of 5th IAPR Int. Conf. on Biometrics (ICB), pages 390–395, Mar. 2012.
E. Hossain and G. Chetty. Multimodal face-gait fusion for biometric person authentication. In Proc. of 9th IFIP Int. Conf. on Embedded and Ubiquitous Computing (EUC), pages 332–337, Oct. 2011.
X. Hou and Z. Liu. Fusion of face and gait for human recognition in video sequences. In Proc. of Int. Conf. on Inf. Technology and Comp. Science (ITCS), volume 1, pages 577–580, Jul. 2009.
A. Jain, A. Ross, and S. Prabhakar. An introduction to biometric recognition. Circuits and Sys. for Video Tech., IEEE Transactions on, 14(1):4–20, Jan 2004.
A. Kale, A. Roychowdhury, and R. Chellappa. Fusion of gait and face for human identification. In Proc. of IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), volume 5, pages V–901–4, May 2004.
B. Kitchenham and S. Charters. Guidelines for performing systematic literature reviews in software engineering, 2007.
Z. Liu and S. Sarkar. Outdoor recognition at a distance by fusing gait and face. Image and Vision Computing, 25(6):817–832, 2007.
L. Qi-Shen, L. Zhi-Tian, and Z. Dan-dan. Integration of gait and side face for human recognition in video. In Proc. of 2nd Int. Symp. on Electronic Commerce and Security (ISECS), volume 2, pages 65–69, May 2009.
A. Ross and A. Jain. Information fusion in biometrics. Pattern Recognition Letters, 24(13):2115–2125, 2003.
G. Shakhnarovich and T. Darrell. On probabilistic combination of face and gait cues for identification. In Proc. of 5th IEEE Int. Conf. on Automatic Face and Gesture Recognition, pages 169–174, May 2002.
G. Shakhnarovich, L. Lee, and T. Darrell. Integrated face and gait recognition from multiple views. In Proc. of IEEE Conf. on Comp. Vision and Pattern Recognition (CVPR), volume 1, pages I–439–I–446, 2001.
X. Xing, K. Wang, and Z. Lv. Fusion of gait and facial features using coupled projections for people identification at a distance. IEEE Signal Processing Letters, 22(12):2349–2353, Dec. 2015.
X. Zhou and B. Bhanu. Feature fusion of face and gait for human recognition at a distance in video. In Proc. of 18th Int. Conf. on Pattern Recognition (ICPR), volume 4, pages 529–532, 2006.
X. Zhou and B. Bhanu. Integrating face and gait for human recognition. In Proc. of Conf. on Comp. Vision and Pattern Recognition Workshop (CVPRW), pages 55–55, Jun. 2006.
X. Zhou and B. Bhanu. Integrating face and gait for human recognition at a distance in video. IEEE Trans. on Sys., Man, and Cyber., Part B: Cyber., 37(5):1119–1137, Oct. 2007.
X. Zhou and B. Bhanu. Feature fusion of side face and gait for video-based human identification. Pattern Recognition, 41(3):778–795, 2008.
X. Zhou, B. Bhanu, and J. Han. Human recognition at a distance in video by integrating face profile and gait. In T. Kanade, A. Jain, and N. Ratha, editors, Audioand Video-Based Biometric Person Authentication, volume 3546 of LNCS, pages 533–543. Springer, 2005.
Publicado
17/05/2016
Como Citar
TELLES, Marcelo Josué; BARBOSA, Jorge Luis Victória; RIGHI, Rodrigo da Rosa.
Um Modelo Computacional para Acessibilidade em Cidades Inteligentes. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 12. , 2016, Florianópolis.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 116-123.
DOI: https://doi.org/10.5753/sbsi.2016.5953.
