A Fuzzy Approach to Spatio-temporal Analysis for Pedestrian Surveillance
Author:
Jain Karan,Raman Rahul
Publisher
Springer Singapore
Reference11 articles.
1. Goto, K., Kidono, K., Kimura, Y., Naito, T.: Pedestrian detection and direction estimation by cascade detector with multi-classifiers utilizing feature interaction descriptor. In: IEEE Intelligent Vehicle Symposium (IV), pp. 224–229 (2011) 2. Tao, J., Klette, R.: Integrated pedestrian direction classification using random decision forest. In: IEEE International Conference on Computer Vision (ICCV) Workshops, pp. 230–237 (2013) 3. Raman, R., Sa, P., Majhi, B., Bakshi, S.: Direction estimation for pedestrian monitoring system in smart cities: an HMM based approach. IEEE Access (2016) 4. Raman, R., Sa, P.K., Bakshi, S., Majhi, B.: Kinesiology-inspired estimation of pedestrian walk direction for smart surveillance. In: Future Generation Computer Systems. North-Holland (2017) 5. Raman, R., Boubchir, L., Sa, P.K., Majhi, B., Bakshi, S.: Beyond estimating discrete directions of walk: a fuzzy approach. In: Machine Vision and Applications. Springer, Berlin (2018)
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