Robust Face Alignment for Illumination and Pose Invariant Face Recognition

In building a face recognition system for real-life scenarios, one usually faces the problem that is the selection of a feature-space and preprocessing methods such as alignment under varying illumination conditions and poses. In this study, we developed a robust face alignment approach based on Active Appearance Model (AAM) by inserting an illumination normalization module into the standard AAM searching procedure and inserting different poses of the same identity into the training set. The modified AAM search can now handle both illumination and pose variations in the same epoch, hence it provides better convergence in both point-to-point and point-to-curve senses. We also investigate how face recognition performance is affected by the selection of feature space as well as the proposed alignment method. The experimental results show that the combined pose alignment and illumination normalization methods increase the recognition rates considerably for all featurespaces. 1

Two dimensional generalized edge detector

Bu çalışmada, daha önce Gökmen ve Jain (1997) tarafından geliştirilen -uzayında görüntü  gösterimi ve ayrıt saptayıcı  iki boyutlu uzaya genişletilmektedir. Bu genişletme özellikle iki açıdan önemlidir. Birinci olarak, görüntülerin -uzayındaki davranışları en iyi, iki boyutlu düzleştirme ve ayrıt saptama süzgeçleri ile modellenebilir. İkincisi, genelleştirilmiş ayrıt saptayıcı (GAS) ile bilinen başarılı birçok ayrıt saptayıcısını üretebildiğinden, iki boyutlu GAS ile bu süzgeçlerin iki boyutlu biçimleri oluşturulabilir. Düzleştirme problemi, zar ve levha modellerinin doğrusal bileşiminden oluşan iki boyutlu karma enerji fonksiyonelinin en aza indirgenmesi olarak tanımlanmıştır. Gökmen ve Jain (1997) karma fonksiyoneli en aza indirgeyen denklemi, ayrıştırılabilir olduğu varsayımı altında tek boyutlu kısmi diferansiyel denklem olarak çözmüşlerdir. Ancak mevcut ayrıştırılabilir çözüm iki boyutlu özgün denklemi sağlamamaktadır. Bu çalışmada, karma fonksiyoneli en aza indirgeyen denklem takımı iki boyutlu uzaydaki çözümü sunulmaktadır. Türetilen süzgeçler önceki süzgeçlerle birinci ve ikinci tür hata karakteristiklerine göre karşılaştırıldığında gürültüye daha az duyar olduğu gözlenmiştir. Gerçek ve yapay görüntüler üzerinde yapılan deneysel sonuçlarla ayrıt saptayıcının performansı ve -uzayındaki davranışı sunulmuştur. Ayrıt saptayıcılar ile çalışırken ayarlanması gereken çok sayıda parametre bulunmaktadır. Verilen bir imge için en iyi parametre kümesini bulmanın genel geçer bir yöntemi bulunmamaktadır. Gerçektende, bir imge için en iyilenen bir ayrıt saptayıcının parametreleri başka bir imge için en iyi olmayacaktır. Bu çalışmada, en iyi GAS parametreleri, verilen bir imge için hesaplanan, alıcı işletim eğrisi üzerinden belirlenmiştir. Burada amaç GAS'ın başarımının sınırlarını göstermektir. Anahtar Kelimeler: Ayrıt saptama, düzenlileştirme kuramı, ölçek-uzayı gösterilimi, yüzey kurma.The aim of edge detection is to provide a meaningful description of object boundaries in a scene from intensity surface. These boundaries are due to discontinuities manifesting themselves as sharp variations in image intensities. There are different sources for sharp changes in images which are created by structure (e.g. texture, occlusion) or illumination (e.g. shadows, highlights). Extracting edges from a still image is certainly the most significant stage of any computer vision algorithm requiring high accuracy of location in the presence of noise. In many contour-based vision algorithms, such as shape-based query, curved-based stereo vision, and edge-based target recognition, their performance is highly dependent on the quality of the detected edges. Therefore, edge detection is an important area of research in computer vision. Despite considerable work and progress made on this subject, edge detection is still a challenging research problem due to the lack of a robust and efficient general purpose algorithm. Most of the efforts in edge detection have been devoted to the development of an optimum edge detector which can resolve the tradeoff between good localization and detection performance. Furthermore, extracting edges at different scales and combining these edges have attracted a substantial amount of interest. In the course of developing optimum edge detectors that can resolve the tradeoff between localization and detection performances, several different approaches have resulted in either a Gaussian filter or a filter whose shape is very similar to a Gaussian. Furthermore, these filters are very suitable for obtaining scale space edge detection since the scale of the filter can be easily controlled by means of a single parameter. For instance, in classical scale-space the kernel is a Gaussian and the scale-space representation is obtained either by convolving the image by a Gaussian with increasing standard deviation or equivalently by solving the linear heat equation in time. This representation is causal, since the isotropic heat equation satisfies a maximum principle. However, the Gaussian scale-space suffers from serious drawbacks such as over-smoothing and location uncertainty along edges at large scales due to interactions between nearby edges and displacements. Although these filters are used widely, it is very difficult to claim that they can provide the desired output for any specific problem. For instance, there are some cases where the improved localization performance is the primary requirement. In these cases, a sub-optimum conditions filter which promotes the localization performance becomes more appropriate. It has been shown that the first order R-filter can deliver improved results on checkerboard and bar images as well as some real images for moderate values of signal-to-noise ratio (SNR). In many vision applications, there is a great demand for a general-purpose edge detector which can produce edge maps with very different characteristics in nature, so that one of these edge maps may meet the requirements of the problem under consideration. Detecting edges in images is one of the most challenging issues in computer vision and image processing due to lack of a robust detector. Gökmen (1997) obtained an edge detector called Generalized Edge Detector (GED), capable of producing most of the existing edge detectors. The original problem was formulated on two-dimensional Hybrid model comprised of the linear combination of membrane and thin-plate functionals. Smoothing problem was then reduced to the solution of two-dimensional partial differential equation (PDE). The filters were obtained for one dimensional case assuming a separable solution. This study extends edge detection of images in lt-space to two-dimensional space. Two-dimensional extension of the representation is important since the properties of images in the space are best modeled by two dimensional smoothing and edge detector filters. Also since GED filters encompass most of the well-known edge detectors, two-dimensional version of these filters could be obtained. The derived filters are more robust to noise when compared to the previous one dimensional scheme in the sense of missing and false alarm characteristics. There are several parameters to tune when dealing with edge detectors. Usually there is no easy way to find the optimal edge detector parameters for an image. In fact, one set of optimal parameters may not be optimal for another image. In this study, we find optimal GED parameters using receiver operator characteristics for an image when its ideal edges are available using exhaustive search to see how best it achieves. Keywords: Edge detection, regularization theory, scale-space representation, surface reconstruction

Aktif görünüm modeline dayalı gürbüz yüz hizalama

In building a face recognition system for real-life scenarios, one usually faces the problem that is the selection of a feature-space and preprocessing methods such as alignment under varying illumination conditions and poses. In this study, we developed a robust face alignment approach based on Active Appearance Model (AAM) by inserting an illumination normalization module into the standard AAM searching procedure and inserting different poses of the same identity into the training set. The modified AAM search can now handle both illumination and pose variations in the same epoch, hence it provides better convergence in both point-to-point and point-to-curve senses. We also investigate how face recognition performance is affected by the selection of feature space as well as the proposed alignment method. The experimental results show that the combined pose alignment and illumination normalization methods increase the recognition rates considerably for all feature spaces. In this paper, we focus on the problems induced by varying illumination and poses. Our primary aim is to eliminate the negative effect of illumination and pose on the face recognition system performance through illumination and pose-invariant face alignment based on Active Appearance Model. Pose normalization is required before recognition in order to reach acceptable recognition rates. We developed AAM based pose normalization method which uses only one AAM. There are two important contributions over the previous studies. By using the proposed method: One can synthetically generate appearances for different poses when only frontal face image is available. One can generate frontal appearance of the face when there is only non-frontal face image is available. The same variation in pose imposes similar effect on the face appearance for all individuals. Deformation mostly occurs on the shape whereas the texture is almost constant. Since the number of landmarks in AAM is constant, the wireframe triangles are translated or scaled as pose changes. So as we change pose, only wireframe triangles undergo affine transformation but the gray level distribution within these triangles remains the same. One can easily generate frontal face appearance if AAM is correctly fitted to any given non-frontal face of the same individual provided that there is no self-occlusion on face. Self-occlusion usually is not a problem for angles less than ±45. For 2D pose generation, we first compute how each landmark point translates and scales with respect to the corresponding frontal counterpart landmark point for 8 different poses, and obtain a ratio vector for each pose. We use the ratio vector to create the same pose variation over the shape of another individual. Appearances are also obtained through AAM using synthetically generated landmarks. It is important to note that the generated faces contain no information about the individual used in building the ratio matrix. An AAM model trained by using only frontal faces can only fit into frontal faces well and fail to fit into non-frontal faces. Our purpose here is to enrich the training database by inserting synthetically generated faces at different poses so that AAM model trained by frontal faces can now converge to images at any pose. In this paper we developed AAM based face alignment method which handles illumination and pose variations. The classical AAM fails to model the appearances of the same identity under different illuminations and poses. We solved this problem by inserting histogram fitting based normalization into the searching mechanism and inserting different poses of the same identity into the training set. From the experimental results, we showed that the proposed face restoration scheme for AAM provides higher accuracy for face alignment in point-to-point error sense. Recognition results based on PCA and LDA feature spaces showed that the proposed illumination and pose normalization outperforms standard AAM. Keywords: Face alignment, active appearance models, illumination invariant face recognition.Yüz görünümündeki şekil ve doku değişimine bağlı farklılıklar yüz tanıma problemini oldukça zor hale getirmektedir. Bireyler arası yüz görünüm farklılıklarının fazla olmasına karşın, her bireyin kendi yüz görünümünü farklı hale getirecek değişimlerde mevcuttur. Özellikle aydınlatma ve poz değişimleri yüz tanıma sistemlerinin başarımını etkileyen zorlukların başında gelmektedir. Bu çalışmada otomatik yüz hizalama için aydınlatma ve poz değişimlerine karşı gürbüz yeni bir yöntem tanıtılmıştır. Klasik aktif görünüm modeli (AGM) yapısına yüz için özelleştirilmiş aydınlatma normalizasyonu eklenerek AGM’nin farklı aydınlatma koşullarındaki arama ve yakınsama performansını arttıran yeni bir yöntem önerilmiştir. AGM ile yüz bölütlemede, özgün yüz aydınlatma normalizasyonunu AGM bükme (warping) işleminden hemen sonra ve her çevirimde uygulayarak aydınlatma değişimlerine karşı gürbüz bir model oluşturulmuştur. Yöntem giriş olarak verilen farklı aydınlatılmış ve farklı bir poza sahip yüz görüntüsünü hem iyileştirmeye hem de hizalamaya çalışmaktadır. Ayrıca tam karşıdan çekilmiş tek bir yüz görüntüsünden, o kişinin farklı pozlara sahip görüntülerini sentezleyen bir yöntem tanıtılmış ve sentetik olarak sentezlenen poz verileri ile AGM şekil uzayı güçlendirilerek poz değişimlerine karşı gürbüz bir yöntem önerilmiştir. Önerilen yöntemde, model eğitimi için aynı bireyin farklı aydınlatma ve poza sahip görüntülerine ihtiyaç duyulmamaktadır. Önerilen yöntemde aydınlatma değişimlerine karşı bağışık bir yapı oluşturulması için karmaşık aydınlatma modelleri gerekmemektedir. Deneysel çalışmalardan da görüleceği gibi önerilen yöntem, farklı aydınlatma ve pozlarda bile klasik AGM’ye göre oldukça iyi sonuçlar vermiştir. Anahtar Kelimeler: Yüz hizalama, aktif görünüm modelleri, aydınlatmadan bağımsız yüz tanıma

Passive sampler derived polychlorinated biphenyls (PCBs) in indoor and outdoor air in Bursa, Turkey: Levels and an assessment of human exposure via inhalation

Although polychlorinated biphenyls (PCBs) were banned several years ago, they can still be measured in the environment, especially in indoors, where their concentrations tend to be higher than outdoors in some cases. The current study reports the results of a study conducted to determine concentrations of a total of 40 PCBs congeners in the living rooms and kitchens of eight different houses, and in the outdoor air of three houses during summer and autumn in Bursa in 2014. The province of Bursa, having eighteen of organized industrial zones, indoor air pollution is of great importance. The average concentration of Sigma(40)PCBs in living rooms and the kitchen were 604 +/- 210 pg/m(3) and 639 +/- 2514 pg/m(3) during summer, respectively; while concentrations in autumn were 362 +/- 167 pg/m(3) and 309 +/- 93 pg/m(3), respectively. The average Sigma(40)PCBs outdoor concentrations were 303 +/- 183 pg/m(3) and 41 +/- 23 pg/m(3) for summer and autumn, respectively. The Sigma(40)PCBs concentrations in summer were almost two times higher than in autumn for indoor environment. The predominant PCB homologs in indoor samples were penta- (40%), tetra- (23%) and tri-CBs (17%) while they were penta- (37%) and tetra-CBs (22%) for outdoor samples. The results of the study indicated the presence of intentionally and unintentionally produced PCBs. The I/O ratios suggested the indoor sites as the most important PCBs source than outdoor sites. Finally, the measured PCB concentrations did not represent a cancer risk for human health for exposure via inhalation in all sampling points

Environmental and human health impacts of usage of oil industry products and wastes as alternative fuel

Hızlı nüfus artışı ve endüstrileşme süreciyle beraber yağ sektörü ürünlerine duyulan ihtiyaç gün geçtikçe artmaktadır. Yağ sektörü ürünleri, kullanıldığı ortam ve koşullara bağlı olarak fiziksel ve kimyasal yapılarında meydana gelen değişiklikler sebebiyle kullanım amacına uygunluğunu kaybederek atık formuna dönüşmektedir. Kalorifik değeri yüksek olan atık yağların bertarafında sıklıkla kullanılan yöntem yakma işlemidir. Bu çalışmada, yağ sektörü ürün ve atıklarının yakılması sonucunda ortaya çıkabilecek emisyonların çevre ve insan sağlığı üzerindeki potansiyel etkilerinin değerlendirilmesi amacıyla ülkemiz özelindeki kullanımlar irdelenmiştir. Yanma olayının uygun olmayan şartlarda gerçekleştirilmesiyle atık yağın yapısında bulunan maddeler ve/veya eksik yanma ürünleri atmosfere salınmaktadır. Yakıtın içeriğine bağlı olarak, partikül madde, karbon monoksit, organik kirleticiler ve metal emisyonları çevresel ortamlara ulaştığında, fizikokimyasal özelliklerine bağlı olarak toprak, su ve hava arasında dağılım gösterebilmektedir. Çevresel ortamlarda oluşturdukları sorunların yanı sıra insan sağlığı üzerinde başta kanserojen ve mutajen etkiler olmak üzere bağışıklık, üreme ve dolaşım sistemi rahatsızlıkları, zehirlenmeler ve ruhsal bozukluklar gibi sorunlara neden olabilmektedir. Ülkemizde, yasal olmamasına rağmen 10 numara yağ adı altında satılan standart dışı dizel muadili yakıtın kullanılması sonucu ortaya çıkan, insan sağlığı ve çevreyi tehdit eden unsurların ortadan kaldırılması için gerekli kontrol ve yasal düzenlemelerin artırılması yerinde olacaktır. Öte yandan, yağ sektörü ürün ve atıklarının yakılmasına dair sorunun boyutu ve dolaylı sağlık etkilerinin belirlenmesi için daha ayrıntılı bileşen analizlerinin yapılması ve alternatif yakma ürünü kullanan araçlarda eş zamanlı kirletici emisyon örneklemesi yapılarak sorunun boyutları ve ortaya çıkaracağı kirleticilerin karakteristikleri ortaya konulmalıdır.The need for oil industry products has increased in parallel to the rapid population growth and industrialization. Physical and chemical properties of these products change after usage based on the media and operating conditions. Then, these products lose the eligibility and turn into the form of waste. The most commonly used method for the disposal of waste oils is combustion due to its high calorific value. In this study, the possible effects on the environment and human health of combustion of oil industry products and wastes are evaluated. Poor combustion conditions lead emissions from the process depending on the ingredients of wastes in addition to incomplete combustion products such as particulate matter, carbon monoxide, volatile organic chemicals polyaromatic hydrocarbons, metals etc. that may occur according to the type of waste. These emissions are released into the environment and partition between soil, water and air media related to their physicochemical characteristics. In addition to environmental problems, these emissions are a risk factor for human health in terms of carcinogenicity and mutagenicity. Regulations and control measures should be put into practice in order to get rid of the effects of non-standard diesel like product named number 10 lube on human health and environment. In this context, emission measurements should be done simultaneously to determine the effects of combustion of these wastes and products of oil industry