TY - GEN
T1 - A computer vision system that ensure the autonomous navigation of blind people
AU - Tapu, Ruxandra
AU - Mocanu, Bogdan
AU - Zaharia, Titus
PY - 2013/12/1
Y1 - 2013/12/1
N2 - In this paper we introduce a real-time obstacle recognition framework designed to alert the visually impaired people/blind of their presence and to assist humans to navigate safely, in indoor and outdoor environments, by handling a Smartphone device. Static and dynamic objects are detected using interest points selected based on an image grid and tracked using the multiscale Lucas-Kanade algorithm. Next, we activated an object classification methodology. We incorporate HOG (Histogram of Oriented Gradients) descriptor into the BoVW (Bag of Visual Words) retrieval framework and demonstrate how this combination may be used for obstacle classification in video streams. The experimental results performed on various challenging scenes demonstrate that our approach is effective in image sequence with important camera movement, including noise and low resolution data and achieves high accuracy, while being computational efficient.
AB - In this paper we introduce a real-time obstacle recognition framework designed to alert the visually impaired people/blind of their presence and to assist humans to navigate safely, in indoor and outdoor environments, by handling a Smartphone device. Static and dynamic objects are detected using interest points selected based on an image grid and tracked using the multiscale Lucas-Kanade algorithm. Next, we activated an object classification methodology. We incorporate HOG (Histogram of Oriented Gradients) descriptor into the BoVW (Bag of Visual Words) retrieval framework and demonstrate how this combination may be used for obstacle classification in video streams. The experimental results performed on various challenging scenes demonstrate that our approach is effective in image sequence with important camera movement, including noise and low resolution data and achieves high accuracy, while being computational efficient.
KW - Bag of Visual Words (BoVW)
KW - Histogram of Oriented Gradients (HOG)
KW - object classification
U2 - 10.1109/EHB.2013.6707267
DO - 10.1109/EHB.2013.6707267
M3 - Conference contribution
AN - SCOPUS:84893799662
SN - 9781479923731
T3 - 2013 E-Health and Bioengineering Conference, EHB 2013
BT - 2013 E-Health and Bioengineering Conference, EHB 2013
T2 - 4th IEEE International Conference on E-Health and Bioengineering, EHB 2013
Y2 - 21 November 2013 through 23 November 2013
ER -