91 research outputs found
Memory-Efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment
Ren et al. recently introduced a method for aggregating multiple decision
trees into a strong predictor by interpreting a path taken by a sample down
each tree as a binary vector and performing linear regression on top of these
vectors stacked together. They provided experimental evidence that the method
offers advantages over the usual approaches for combining decision trees
(random forests and boosting). The method truly shines when the regression
target is a large vector with correlated dimensions, such as a 2D face shape
represented with the positions of several facial landmarks. However, we argue
that their basic method is not applicable in many practical scenarios due to
large memory requirements. This paper shows how this issue can be solved
through the use of quantization and architectural changes of the predictor that
maps decision tree-derived encodings to the desired output.Comment: BMVC Newcastle 201
Representation of the Consumer Interest in the Federal Government
We describe a method for eye pupil localization based on an ensemble of randomized regression trees and use several publicly available datasets for its quantitative and qualitative evaluation. The method compares well with reported state-of-the-art and runs in real-time on hardware with limited processing power, such as mobile devices
Visualization Techniques for Surveillance: Visualizing What Cannot Be Seen and Hiding What Should Not Be Seen
Прусское чиновничество: от военизированной службы к рациональному управлению
This work examines the possiblity to, with the computational power of today’s consumer hardware, employ techniques previously developed for 3D tracking of rigid objects, and use them for tracking of deformable objects. Our target objects are human faces in a video conversation pose, and our purpose is to create a deformable face tracker based on a head tracker operating in real-time on consumer hardware. We also investigate how to combine model-based and image based tracking in order to get precise tracking and avoid drift
Health safety on plastic materials that come into contact with food and children toys about migration of primary aromatic amines examination in IPH- Skopje in period 01.01.2013 – 31.12.2013
Humans can be exposed to primary aromatic amines (PAAs) by the usage of a variety of synthetic products which come in contact with food and plastic children toys. PAAs are mainly originated from synthetic azo dyes widely applied as colorants on plastics and also from the use of adhesives based on polyurethanes (PU) in laminated food packing materials. Legislation introduced in the European Union countries limiting the migration level of PAAs into foodstuffs is 0.01 mg/kg. Aim of the study was establishing method for routine examination of PAAs in items made of plastics that come into direct contact with food and plastic toys.
Material and Methods: Quantitative determination of sum of PAAs, expressed as aniline on 727 items of which 363 plastic toys, and 364 plastic containers, plastic utensils and plastic items that come in direct contact with food. Was using spectrophotometric method based on diazotization of PAAs and subsequent coupling of the obtained diazonium salts with N-(1-naphthyl) ethylenediamine dihydrochloride.
Calibration was carried out using known amounts of aniline hydrochloride as standard. Detection limit (DL) and quantification limit (QL) evaluated for direct spectrophotometric method amounted to 0,000715 mg/l and 0,002165 mg/l, respectively. Only 6 tested samples were not correct in terms of increased concentration of PAAs in simulant solution. From the faulty samples 4 were toys, and 2 black kitchen sets which coming in contact with food. Conclusion: Requires increased sanitary inspection market, amid frequent occurrence of PAAs in plastic kitchen utensils, especially kitchen utensils in black and children toys made in China.
Keywords: Food Contact Materials (FCM), Toys, Primary Aromatic Amines (PAAs), Migration, Safet
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