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Interactive Object Counting
Carlos Arteta1, Victor Lempitsky2, J. Alison Noble1, and Andrew Zisserman1
1Department of Engineering Science, University of Oxford, UK
2Skolkovo Institute of Science and Technology (Skoltech), Russia
Abstract. Our objective is to count (and localize) object instances in an image interactively. We target the regime where individual object detectors do not work reliably due to crowding, or overlap, or size of the instances, and take the approach of estimating an object density.
Our main contribution is an interactive counting system, along with solutions for its main components. Thus, we develop a feature vocabulary that can be efficiently learnt on-the-fly as a user provides dot annotations – this enables densities to be generated in an interactive system. Furthermore, we show that object density can be estimated simply, accurately and efficiently using ridge regression – this matches the counting accuracy of the much more costly learning-to-count method. Finally, we propose two novel visualization methods for region counts that are efficient and effective – these enable integral count regions to be displayed to quickly determine annotation points for relevance feedback.
The interactive system is demonstrated on a variety of visual material, including photographs, microscopy and satellite images.
Keywords: Interactive vision systems, object counting, relevance feedback, visual recognition, biomedical image analysis
LNCS 8691, p. 504 ff.
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© Springer International Publishing Switzerland 2014