Roadside Data

Roadside Data

1.           Aristidou, A. and J. Lasenby, Real-time marker prediction and CoR estimation in optical motion capture. User Modeling and User-Adapted Interaction, 2013. 29: p. 7-26.

2.           Shankar, S., J. Lasenby, and A. Kokaram, Warping trajectories for video synchronization, in Proceedings of the 4th ACM/IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Stream, ARTEMIS 2013. 2013. p. 41-48.

3.           Shankar, S., J. Lasenby, and R. Cipolla, Semantic transform: Weakly supervised semantic inference for relating visual attributes, in Proceedings of the IEEE International Conference on Computer Vision. 2013. p. 361-368.

4.           Shankar, S., J. Lasenby, and A. Kokaram, Synchronization of user-generated videos through trajectory correspondence and a refinement procedure, in ACM International Conference Proceeding Series. 2013.

5.           Wareham, R., Can we predict England’s traffic?, 2014.

6.           Wareham, R. and N. Kingsbury. Finding Patterns and Predicting England’s Traffic. , 2014, University of Cambridge.

7.           Wareham, R. and N. Kingsbury, Dualtree Complex Wavelet Methods for Optical Tracking of Road Vehicles, in BMVC 2015. 2015: Swansea, UK.

8.           Wareham, R. and N. Kingsbury. Viewpoint Independent Vehicles, 2015, Zenodo: Poster published at SRF Annual Conference.

9.           Wareham, R., T. Roberts, and S. Forshaw, The Dual Tree Complex Wavelet transform library. 2015.

10.         Wareham, R., F. S., and N. Kingsbury, Simultaneous video of a traffic junction from two viewpoints. 2015, University of Cambridge,

11.         Burke, M. and J. Lasenby, Estimating missing marker positions using low dimensional Kalman smoothing. J Biomech, 2016. 49: p. 1854-1858.

12.         Wareham, R., Starman: a Kalman filtering library. 2016, Zenodo.

13.         Wareham, R., R. T., and F. S., The python-dtcwt package, G.A. Vaillant, Editor. 2016, Debian Science Maintainers.