Margarita Osadchy

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We describe a novel method for real-time, simultaneous multi-view face detection and facial pose estimation. The method employs a convolutional network to map face images to points on a manifold, parametrized by pose, and non-face images to points far from that manifold. This network is trained by optimizing a loss function of three variables: image, pose,(More)
We introduce SCiFI, a system for Secure Computation of Face Identification. The system performs face identification which compares faces of subjects with a database of registered faces. The identification is done in a secure way which protects both the privacy of the subjects and the confidentiality of the database. A specific application of SCiFI is(More)
In some capturing devices, such as digital cameras, there is only one color sensor at each pixel. Usually, 50% of the pixels have only a green sensor, 25% only a red sensor, and 25% only a blue sensor. The problem is then to restore the two missing colors at each pixel – this is called “demosaicing”, because the original samples are usually arranged in a(More)
We consider the problem of matching images to tell whether they come from the same scene viewed under different lighting conditions. We show that the surface characteristics determine the type of image comparison method that should be used. Previous work has shown the effectiveness of comparing the image gradient direction for surfaces with material(More)
ÐThis paper offers a novel detection method, which works well even in the case of a complicated image collectionÐfor instance, a frontal face under a large class of linear transformations. It is also successfully applied to detect 3D objects under different views. Call the collection of images, which should be detected, a multitemplate. The detection(More)
To study the protein structure-function relationship, we propose a method to efficiently create three-dimensional maps of structure space using a very large dataset of > 30,000 Structural Classification of Proteins (SCOP) domains. In our maps, each domain is represented by a point, and the distance between any two points approximates the structural distance(More)
Biometric authentication is more secure than using regular passwords, as biometrics cannot be "forgotten" and contain high entropy. Thus, many constructions rely on biometric features for authentication, and use them as a source for "good" cryptographic keys. At the same time, biometric systems carry with them many privacy concerns. We describe a(More)
Most effective face recognition methods store biometric information in the clear. Doing so exposes those systems to the risk of identity theft and violation of privacy. This problem significantly narrows the practical use of face recognition technology. Recent methods for privacy preserving face recognition address face verification task. Most of them are(More)
We present a novel approach to pose estimation and model-based recognition of specular objects in difficult viewing conditions, such as low illumination, cluttered background, large highlights, and shadows that appear on the object of interest. In such challenging conditions, conventional features are unreliable. We show that under the assumption of a(More)