We propose a scheme for indoor place identication based on the recognition of global scene
views. Scene views are encoded using a holistic representation that provides low-resolution
spatial and spectral information. The holistic nature of the representation dispenses with the
need to rely on specic objects or local landmarks and also renders it robust against variations
in object congurations. We demonstrate the scheme on the problem of recognizing scenes in
video sequences captured while walking through an oÆce environment. We develop a method
for distinguishing between 'diagnostic' and 'generic' views and also evaluate changes in system
performances as a function of the amount of training data available and the complexity of the
representation.
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Antonio B. Torralba, Ariadna Quattoni