Fast Face Detector Training Using Tailored Views

Face detection is an important task in computer vision and often serves as the first step for a variety of applications. State-of-the-art approaches use efficient learning algorithms and train on large amounts of manually labeled imagery. Acquiring appropriate training images, however, is very time-consuming and does not guarantee that the collected training data is representative in terms of data variability. Moreover, available data sets are often acquired under con-trolled settings, restricting, for example, scene illumination or 3D head pose to a narrow range. This paper takes a look into the automated generation of adaptive training samples from a 3D morphable face model. Using statistical insights, the tailored training data guarantees full data variability and is enriched by arbitrary facial attributes such as age or body weight. Moreover, it can automatically adapt to environmental constraints, such as illumination or viewing angle of recorded video footage from surveillance cameras. We use the tailored imagery to train a new many-core imple-mentation of Viola Jones ’ AdaBoost object detection frame-work. The new implementation is not only faster but also enables the use of multiple feature channels such as color features at training time. In our experiments we trained seven view-dependent face detectors and evaluate these on the Face Detection Data Set and Benchmark (FDDB). Our experiments show that the use of tailored training imagery outperforms state-of-the-art approaches on this challenging dataset. 1

Leukoencephalopathy upon disruption of the chloride channel ClC-2

ClC-2 is a broadly expressed plasma membrane chloride channel that is modulated by voltage, cell swelling, and pH. A human mutation leading to a heterozygous loss of ClC-2 has previously been reported to be associated with epilepsy, whereas the disruption of Clcn2 in mice led to testicular and retinal degeneration. We now show that the white matter of the brain and spinal cord of ClC-2 knock-out mice developed widespread vacuolation that progressed with age. Fluid-filled spaces appeared between myelin sheaths of the central but not the peripheral nervous system. Neuronal morphology, in contrast, seemed normal. Except for the previously reported blindness, neurological deficits were mild and included a decreased conduction velocity in neurons of the central auditory pathway. The heterozygous loss of ClC-2 had no detectable functional or morphological consequences. Neither heterozygous nor homozygous ClC-2 knock-out mice had lowered seizure thresholds. Sequencing of a large collection of human DNA and electrophysiological analysis showed that several ClC-2 sequence abnormalities previously found in patients with epilepsy most likely represent innocuous polymorphisms

Sequestration of cholesterol within the host late endocytic pathway restricts liver-stage Plasmodium development

While lysosomes are degradative compartments and one of the defenses against invading pathogens, they are also hubs of metabolic activity. Late endocytic compartments accumulate around Plasmodium berghei liver-stage parasites during development, and whether this is a host defense strategy or active recruitment by the parasites is unknown. In support of the latter hypothesis, we observed that the recruitment of host late endosomes (LEs) and lysosomes is reduced in uis4(−) parasites, which lack a parasitophorous vacuole membrane protein and arrest during liver-stage development. Analysis of parasite development in host cells deficient for late endosomal or lysosomal proteins revealed that the Niemann–Pick type C (NPC) proteins, which are involved in cholesterol export from LEs, and the lysosome-associated membrane proteins (LAMP) 1 and 2 are important for robust liver-stage P. berghei growth. Using the compound U18666A, which leads to cholesterol sequestration in LEs similar to that seen in NPC- and LAMP-deficient cells, we show that the restriction of parasite growth depends on cholesterol sequestration and that targeting this process can reduce parasite burden in vivo. Taken together, these data reveal that proper LE and lysosome function positively contributes to liver-stage Plasmodium development

Removing pose from face images

This paper proposes a novel approach to pose removal from face images based on the inherent symmetry that is present in faces. In order for face recognition systems and expression classification systems to operate optimally, subjects must look directly into the camera. The removal of pose from face images after their capture removes this restriction. To obtain a pose-removed face image, the frequency components at each position of the face image, obtained through a wavelet transformation, are examined. A cost function based on the symmetry of this wavelet transformed face image is minimized to achieve pose removal.Experimental results are presented that demonstrate that the proposed algorithm improves upon existing techniques in the literature

Automatic 3D facial model and texture reconstruction from range scans

This paper presents a fully automatic approach to fitting a generic facial model to detailed range scans of human faces to reconstruct 3D facial models and textures with no manual intervention (such as specifying landmarks). A Scaling Iterative Closest Points (SICP) algorithm is introduced to compute the optimal rigid registrations between the generic model and the range scans with different sizes. And then a new template-fitting method, formulated in an optmization framework of minimizing the physically based elastic energy derived from thin shells, faithfully reconstructs the surfaces and the textures from the range scans and yields dense point correspondences across the reconstructed facial models. Finally, we demonstrate a facial expression transfer method to clone facial expressions from the generic model onto the reconstructed facial models by using the deformation transfer technique