Video-based methods such as tracking and appearance recognition can be used in the public transport domain to re-acquire an estimate of the whereabouts of a passenger of interest. Starting with the end user requirements, it is argued that the most appropriate performance metric with which to evaluate these methods, is to measure the information gained through their use. This is equivalent to the reduction in uncertainty about the passenger's whereabouts, after tracking and appearance-based measurements are used to update the estimates of which detected persons are likely to be the passenger of interest. The prior estimates are significantly conditioned on the statistics for the likely distributions for entry and traversal through the network: a simple model is described for this purpose. The suitability of tracking and appearance based matching methods are discussed in this context.
['Valerie Leung', 'James Orwell', 'Sergio A. Velastin']
Performance evaluation of re-acquisition methods for public transport surveillance