Deep filter banks for texture recognition, description, and segmentation

Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common texture patterns, complemented by a new describable texture dataset for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture representations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as filter banks. We obtain in this manner state-of-the-art performance in numerous datasets well beyond textures, an efficient method to apply deep features to image regions, as well as benefit in transferring features from one domain to another.Comment: 29 pages; 13 figures; 8 table

Efficiency losses in milk marketing boards – the importance of exports

A milk marketing board (MMB) is a legislatively specified compulsory marketing institution, and a common way to regulate markets for dairy products. MMBs are based on price discrimination. As price discrimination leads to unequal profitability between products, receipts from sales are pooled and farmers receive a single price adjusted for composition and quality. It is well documented that price discrimination through MMBs incurs an efficiency loss to the society. Earlier contributions, Ippolito and Masson (1978) and Serck-Hansen (1979), point to the fact that a particular high loss is incurred if export of dairy products is included in the MMB. It proves difficult to find examples where this is the case. MMB countries are either large with a low export share in dairy products (USA and Japan), have economies of scale (Australia) or exports are excluded from the MMB arrangement (Canada). We find Norway to be the only example. Using a numerical model of the Norwegian agricultural sector we show that substantial efficiency gain may be achieved by deregulating the dairy sector, mainly due to the elimination of exports. It is estimated that a transition to cost based pricing may increase the economic surplus by 1.4 billion NOK, which is 25 % of the production value. This computed gain from deregulation is far larger than for the other MMB-countries.Dairy policy; milk marketing boards; price discrimination; deregulation; numerical model.