Real Time Machine Learning Based Car Detection in Images With Fast Training

Our primary interest is to build fast and reliable object recognizers in images based on small training sets. This is important in cases where the training set needs to be built mostly manually, as in the case that we studied, the recognition of the Honda Accord 2004 from rear views. We describe a novel variant of the AdaBoost based learning algorithm, which builds a strong classifier by incremental addition of weak classifiers (WCs) that minimize the combined error of the already selected WCs. Each WC is trained only once, and examples do not change their weights. We describe a set of appropriate feature types for the considered recognition problem, including a redness measure and dominant edge orientations. The existing edge orientation bin division was improved by shifting so that all horizontal (vertical, respectively) edges belong to the same bin. We propose to pre-eliminate features whose best threshold value is near the trivial position at the minimum or maximum of all threshold values. This is a novel method that has reduced the training set WC quantity to less than 10% of its original number, greatly speeding up training time, and showing no negative impact on the quality of the final classifier. We also modified the AdaBoost based learning machine. Our experiments indicate that the set of features used by Viola and Jones and others for face recognition was inefficient for our problem, recognizing cars accurately and in real time with fast training. Our training method has resulted in finding a very accurate classifier containing merely 30 WCs after about 1 h of training. Compared to existing literature, we have overall achieved the design of a real time object detection machine with the least number of examples, the least number of WCs, the fastest training time, and with competitive detection and false positive rates.     

A case of using the Semantic Interoperability Framework for custom orthopedic implants manufacturing

The efficiency and effectiveness of the daily practice in orthopedic surgery depend on the availability, interoperability and unique access to a wide set of information, related to the patient’s medical record and diagnosis, domain knowledge and available resources and staff. The most important of the tangible resources, needed for the therapeutic or preventive actions are orthopedic implants. In some cases, the implants may be highly complex and customized products, which need to be manufactured (assembled) on basis of the above information in a shortest possible timeframe. In this paper, the case of the custom orthopedic implants manufacturing is described from the perspective of the collaborative enterprising, with special consideration of the interoperability issues of the involved enterprise collaboration. It is shown how the previously developed Semantic Interoperability Framework can be used to improve the efficiency of the manufacturing and other relevant processes.     

Identification and changes in the higher fatty acids of dried red pepper and red pepper powder

Summary The higher fatty acids of dried red pepper of the variety of Gorogled were identified by gas chromatography with using help of authentic compounds. Their amounts were determined using on absolute calibration method.The following acids were established: lauric, myrastic, palmitic, palmitoleic, stearic, oleic, linoleic, linolenic,arachidic and behenic acids. The results obtained from the quantitative measurements showed that linoleic, linolenic and palmitic acids amounted to 80% of the total acids.The quantitative changes of identified acids in red pepper, of dried at 60°, 70°, 80° and 90 °C red pepper and stored as dried red pepper and red pepper powder over a 6-months period investigated.The results show that under the drying temperatures applied the amount of all fatty acids decreased with an increase in the temperature. During a storage a period of 3 months the amount of the respective acids decreased while the process was the most expressed in red pepper dried at a temperature of t = 70 °C.After a 6-months storage period under the drying condition applied the dried red pepper contained a greater amount of fatty acids compared with stored for 3 months.

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Identifikation und Veränderungen der höheren Fettsäuren von gemahlenem Paprika und von getrockneten ungemahlenen Paprikaschoten

Zusammenfassung Es wurden gaschromatographisch mit Hilfe von Vergleichsubstanzen die höheren Fettsäuren, die im gemahlenen Paprika (Sorte Gorogled) enthalten sind, identifiziert. Die Mengen wurden nach der Methode der absoluten Kalibrierung bestimmt. Es wurden folgende Säuren festgestellt: Laurinsäure, Myristin-, Palmitin-, Palmitoolein-, Stearin-, Olein-, Linol-, Linolen-, Arachin- und Behensäure. Die quantitativen Ergebnisse zeigen, daß die Menge der Linolen-, Linol- und Palmitinsäure 80% der Gesamtsäurenmenge darstellt. Es wurden die quantitativen Veränderungen der Fettsäuren von Paprika (Sorte Gorogled) bei Temperaturen von 60 °, 70 °, 80 ° und 90 °C, getrocknet und als getrockneter ungemahlener bzw.gemahlener Paprika, gelagert und innerhalb von 6 Monaten in Abständen von 3 Monaten verfolgt. Bei den angewendeten Trocknungstemperaturen nimmt die Menge der einzelnen Fettsäuren in dem getrockneten ungemahlenen Paprika mit Erhöhung der Trocknungstemperatur ab. Die Lagerung des getrockneten ungemahlenen Paprikas innerhalb von 3 Monaten führt zur Abnahme der einzelnen Fettsäuren, wobei dieser Prozeß am stärksten bei einer Trocknungstemperatur von 70 °C verläuft. Nach einer 6monatigen Lagerung des getrockneten und ungemahlenen Paprikas, nach Trocknung und bei den o. g. vier Temperaturen, ist die Menge der Fettsäuren höher im Vergleich zu jener der Fettsäuren in getrocknetem ungemahlenem Paprika nach 3 Monaten. Nach 3 Monaten enthält der gemahlene Paprika weniger Fettsäuren als der getrocknete und ungemahlene Paprika.

     

On the role of hydrophilicity and hydrophobicity in aqueous heterophase polymerization

This paper reports on experimental results of aqueous heterophase polymerizations with monomers of quite different solubility in water ranging from the water-soluble 2-hydroxyethyl methacrylate to lauryl methacrylate with solubility in water of only about 10⁻⁴ mM. A calorimetric study revealed the strong influence of both the hydrophilicity of the monomer and the stirrer speed on the rate of polymerization in the absence of surfactants. In order to obtain maximum latex yield and high efficiency (which is a measure considering colloidal properties, polymerization recipe, and polymerization parameters) the initiator-surfactant combination must be properly chosen in dependence on the hydrophilicity of the monomer. Results are presented for sodium alkyl sulfates or disodium-N-stearoyl-l-glutamate as surfactant and potassium peroxodisulfate, or poly(ethylene glycol)-azo- compounds, or 2,2′-azobis(N-2′-methylpropanoyl-2-amino-alkyl-1)-sulfonates as initiators.     

An alignment-free fingerprint bio-cryptosystem based on modified Voronoi neighbor structures

Bio-cryptography is an emerging security technology which combines cryptography with biometrics. A good bio-cryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in bio-cryptosystem design. However, fingerprint uncertainty caused by distortion and rotation during the image capturing process makes it difficult to achieve a high recognition rate in most bio-cryptographic systems. Moreover, most existing bio-cryptosystems rely on the accurate detection of singular points for fingerprint image pre-alignment, which is very hard to achieve, and the image rotation transformation during the alignment process can cause significant singular point deviation and minutiae changes. In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignment-free bio-cryptosystem based on fixed-length bit-string representations extracted from modified VNSs, which are rotation- and translation-invariant and distortion robust. The proposed alignment-free bio-cryptosystem is able to provide strong security while achieving good recognition performance. Experimental results in comparison with most existing alignment-free bio-cryptosystems using the publicly-available databases show the validity of the proposed scheme.     

Automatic player position detection in basketball games

This paper presents us with a framework for the automatic player position detection (APPD) in the game of basketball. Court players are detected in the images broadcasted via television stations. In them, at any point of time, the view is from only one camera. This makes the detection process much more difficult. The player detection is based on the mixture of non-oriented pictorial structures. The detection of body parts is performed by the Support Vector Machine (SVM) algorithm. The results of these detections are combined together with constraints on their locations, which specify the position of one body part with respect to the parent body part. In order to train the whole model, we used a latent form of SVM called the latent SVM (LSVM). Such approach generated the statistical accuracy of about 82 %, which represents one of the best results in basketball player detection framework. Beside players, the algorithm detected a certain number of false positive objects. These are mostly people from the audience and the referees as well. This paper contains a simple and robust solution to remove them all, based on the play court boundaries and the histogram comparison. Separating players in different teams is done by k-means clustering. The inputs to this algorithm are saturation histograms calculated on the jerseys. A spatial transformation is determined by the detected play court boundaries and the actual court measures. Using this transformation, points representing the location of detected players in TV images are mapped to the actual location of players on the court, which was the main goal of our research. The proposed solution is sound and efficient. In addition, it is backed up by the experimental results obtained using the model of the actual footage of basketball games.     

Mit zweierlei Maß: Die mangelnde Verbindlichkeit von Patientenverfügungen bei untergebrachten Personen mit psychischen Störungen in der Schweiz

Definition of the problem

Full age patients with mental disorders and preserved decision-making capacity are increasingly interested in drafting advance directives. Whereas in Switzerland (as well as in Germany) advance directives are binding in principle, an advance directive is not binding and has only to be considered in case of involuntary admission due to a mental disorder. Thereby, the virtual aim of an advance directive – the anticipated self-determination – is questioned.

Arguments

From an ethical perspective, patients with mental disorders have the same rights as patients with somatic diseases. Therefore, the question arises if there are good reasons for this unequal treatment. In the present contribution, four possible reasons are analyzed: (1) persons with mental disorders are “different”; (2) protection from self-harm; (3) often not present end-of-life context; (4) reduced bindingness as the more appropriate standard in general.

Conclusion

The authors come to the conclusion that patients with mental disorders are often capable of composing a valid advance directive, and just as any other human being, they have a principal and binding right for self-determination, even though they are particularly vulnerable in crisis situations.

     

混合的SAR图像变化检测算法

为尽可能多地消除遥感图像变化检测过程中“伪变化”信息的影响,获得比较客观的感兴趣区域变化检测结果,针对遥感图像中SAR图像的特点,提出一种混合的SAR图像变化检测算法。对已配准好的图像进行Frost滤波,用邻域比值的方法构造差异图,对得到的差异图进行非下采样轮廓波变换（NSCT）,对变换得到的高频子带和低频子带分别处理,用模糊C均值（FCM）聚类算法得到变化检测的结果。实验结果表明,该算法模型很好地保留了图像变化区域的细节,提高了变化检测准确性。     

Identification and optimization of key process parameters in noncontact laser scanning for reverse engineering

This Extended Technical Note shows that the final accuracy level of reverse engineered surfaces depends on scanning distance and scanning angle of the laser beam, hence it also depends on the morphology of the scanned objects. On scanning strongly curved objects, such as the ones with free form surfaces, the distance and impact angle of the laser beam are changing continuously during the scanning process. On the basis of these, two critical parameters are specified for the design model, which make it possible to predict these two factors in advance, depending on the morphology of the scanned object. First, a mathematical-statistical design model of the scanning process is generated, which relies on ANOVA (analysis of variance) and DOE (design of experiments). In the next step, a fitness function is optimized by the genetic algorithm (GA) program. This optimization improves the accuracy of the final scanned surfaces, in terms of the minimum standard deviation values of reverse engineered 3D surface model. The proposed approach was confirmed in a case study, which is presented at the end of this Technical Note.