Artículos de revistas
A Kinect-based Wearable Face Recognition System To Aid Visually Impaired Users
Registro en:
Ieee Transactions On Human-machine Systems. Ieee-inst Electrical Electronics Engineers Inc, v. 47, p. 52 - 64, 2017.
2168-2291
2168-2305
WOS:000396400300006
10.1109/THMS.2016.2604367
Autor
Neto
Laurindo Britto; Grijalva
Felipe; Margareth Lima Maike
Vanessa Regina; Martini
Luiz Cesar; Florencio
Dinei; Calani Baranauskas
Maria Cecilia; Rocha
Anderson; Goldenstein
Siome
Institución
Resumen
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) In this paper, we introduce a real-time face recognition (and announcement) system targeted at aiding the blind and low-vision people. The system uses a Microsoft Kinect sensor as a wearable device, performs face detection, and uses temporal coherence along with a simple biometric procedure to generate a sound associated with the identified person, virtualized at his/her estimated 3-D location. Our approach uses a variation of the K-nearest neighbors algorithm over histogram of oriented gradient descriptors dimensionally reduced by principal component analysis. The results show that our approach, on average, outperforms traditional face recognition methods while requiring much less computational resources (memory, processing power, and battery life) when compared with existing techniques in the literature, deeming it suitable for the wearable hardware constraints. We also show the performance of the system in the dark, using depth-only information acquired with Kinect's infrared camera. The validation uses a new dataset available for download, with 600 videos of 30 people, containing variation of illumination, background, and movement patterns. Experiments with existing datasets in the literature are also considered. Finally, we conducted user experience evaluations on both blindfolded and visually impaired users, showing encouraging results. 47 1 52 64 Microsoft-Sao Paulo Research Foundation (FAPESP) [2012/50468-6] Unicamp Institutional Review Board [CAAE 15641313.7.0000.5404, CAAE 31818014.0.0000.5404] CNPq [141254/2014-9, 308618/2014-9, 304352/2012-8, 308882/2013-0, 304472/2015-8, 477662/2013-7] FAPESP [2014/14630-9, 2013/21349-1, 2015/19222-9] DejaVu project [2015/19222-9] CAPES [01-P-04554/2013] CAPES DeepEyes project Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)