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Network Modeling Analysis in Health Informatics and Bioinformatics
Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics 2/2013

01.07.2013 | Original Article

Finding objects for assisting blind people

verfasst von: Chucai Yi, Roberto W. Flores, Ricardo Chincha, YingLi Tian

Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics | Ausgabe 2/2013

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Abstract

Computer vision technology has been widely used for blind assistance, such as navigation and way finding. However, few camera-based systems are developed for helping blind or visually impaired people to find daily necessities. In this paper, we propose a prototype system of blind-assistant object finding by camera-based network and matching-based recognition. We collect a dataset of daily necessities and apply Speeded-Up Robust Features and Scale Invariant Feature Transform feature descriptors to perform object recognition. Experimental results demonstrate the effectiveness of our prototype system.
Vorheriger Artikel Monitoring activity of taking medicine by incorporating RFID and video analysis
Nächster Artikel Detecting signage and doors for blind navigation and wayfinding

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Literatur
Bay H, Tuytelaars T, Van Gool L (2006) SURF: speeded up robust features. European Conference on Computer Vision
Biederman I (1987) Recognition-by-components: a theory of human image understanding. Psychol Rev 94:115–147CrossRef
Bobo B, Chellapa R, Tang C (2008) Developing a real-time identify-and-locate system for the blind. In: Workshop on computer vision applications for the visually impaired
Gehring S (2008) Adaptive indoor navigation for the blind. Proc GI Jahrestagung 1:293–294
Hoover A, Olsen B (2000) Sensor network perception for mobile robotics. IEEE Int Conf Robotics Autom 1:342–347
Hub A, Diepstraten J, Ertl T (2004) Design and development of an indoor navigation and object identification system for the Blind. In: Proceedings of ASSETS, pp 147–152
Hub A, Hartter T, Ertl T (2006) Interactive tracking of movable objects for the blind on the basis of environmental models and perception oriented object recognition methods. In: Proceedings of ASSETS, pp 111–118
Hung C, Kreiman G, Poggio T, DiCarlo J (2005) Fast read-out of object identity from Macaque inferior temporal cortex. Science 310:863–866CrossRef
Husle J, Khoshgoftaar M, Napolitano A, Wald R (2012) Threshold-based feature selection techniques for high-dimensional bioinformatics data. Netw Model Anal Health Inform Bioinform 1(1–2):47–61
Jauregi E, Lazkano E, Sierra B (2009) Object recognition using region detection and feature extraction. In: Proceedings of towards autonomous robotic systems (TAROS) (ISSN: 2041-6407)
Kao G, Probert P, Lee D (1996) Object recognition with FM sonar: an assistive device for blind and visually-impaired people. AAAI fall symposium on developing assistive technology for people with disabilities. MIT, Cambridge
Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vision
Marinakis D, Dudek G (2005) Topology inference for a vision-based sensor network. In: Proceedings of Canadian conference on computer and robot vision, pp 121–128
Nikolakis G, Tzovaras D, Strintzis MG (2005) Object recognition for the blind. In: Proceedings of 13th European signal processing conference (EUSIPCO 2005). Antalya, Turkey
Orwell J, Lowey L, Thirde D (2005) Architecture and algorithms for tacking footable players with multiple cameras. IEEE Proc Vision Image Signal Process 152(2):232–241CrossRef
Potter M, Levy E (1969) Recognition memory for a rapid sequence of pictures. J Exp Psychol 81:10–15CrossRef
Sudol J, Dialameh O, Blanchard C, Dorcey T (2010) LookTel—a comprehensive platform for computer-aided visual assistance. IEEE Conference on Computer Vision and Pattern Recognition
Ta DN, Chen WC, Gelfand N, Pulli K (2009) SURFTrac: efficient tracking and continuos object recognition using local feature descriptors. IEEE Conference on Computer Vision and Pattern Recognition, pp 2937–29
Tang W, Su D (2012) Locomotion analysis and its applications in neurological disorders detection: state-of-art review. Network Model Anal Health Inform Bioinform
Thorpe S, Fize D, Marlot C (1996) Speed of processing in the human visual system. Nature 381:520–522CrossRef
Wang S, Yi C, Tian Y (2012) Signage detection and recognition for blind persons to access unfamiliar environment. J Comput Vision Image Process 2(2)
Xiang Y, Fuhry D, Kaya K, Jin R, Catalyurek U, Huang K (2012) Merging network patterns: a general framework to summarize biomedical network data. 1(3): 103–116
Xie D, Yan T, Ganesan D, Hanson A (2008) Design and implementation of a dual-camera wireless sensor network for object retrieval. In: Proceedings of the 7th international conference on information processing in sensor networks, pp 469–480
Yu G, Morel J.-M (2011) ASIFT: an algorithm for fully affine invariant comparison. Image Process On Line, 2011
Metadaten
Titel
Finding objects for assisting blind people
verfasst von
Chucai Yi
Roberto W. Flores
Ricardo Chincha
YingLi Tian
Publikationsdatum
01.07.2013
Verlag
Springer Vienna
Erschienen in
Network Modeling Analysis in Health Informatics and Bioinformatics / Ausgabe 2/2013
Print ISSN: 2192-6662
Elektronische ISSN: 2192-6670
DOI
https://doi.org/10.1007/s13721-013-0026-x

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