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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 unable to generalize to unseen conditions...
Facial image analysis is an important computer vision topic as a first step for biometric applications like face recognition/verification. The ICAO specification defines criteria to assess suitability of facial images for later use in such tasks. This standard prohibits photographs showing occlusions, thus there is the need to detect occluded images automatically. In this work we present a novel algorithm...
Recently, combining information from multiple cameras has shown to be very beneficial for object detection and tracking. In contrast, the goal of this work is to train detectors exploiting the vast amount of unlabeled data given by geometry information of a specific multiple camera setup. Starting from a small number of positive training samples, we apply a co-training strategy in order to generate...
CAMShift is a well-established and fundamental algorithm for kernel-based visual object tracking. While it performs well with objects that have a simple and constant appearance, it is not robust in more complex cases. As it solely relies on back projected probabilities it can fail in cases when the object's appearance changes (e.g., due to object or camera movement, or due to lighting changes), when...
This paper proposes a new method for estimating and maintaining over time the pose of a single Pan-Tilt-Zoom camera (PTZ). This is achieved firstly by building offline a keypoints database of the scene; then, in the online step, a coarse localization is obtained from camera odometry and finally refined by visual landmarks matching. A maintenance step is also performed at runtime to keep updated the...
We propose a structural image representation and show its relevance for multi-modal image registration. Structural representation means that only the structures in the image matter and not the intensity values of their depiction. The representation is formulated as a dense descriptor. We specify three properties an optimal descriptor for structural registration has to fulfill: locality preservation,...
This paper presents a view-invariant approach to gait recognition in multi-camera scenarios exploiting a joint spatio-temporal data representation and analysis. First, multi-view information is employed to generate a 3D voxel reconstruction of the scene under study. The analyzed subject is tracked and its centroid and orientation allow recentering and aligning the volume associated to it, thus obtaining...
This paper presents the first investigation into the classification of faces from unconstrained video sequences in natural scenes, i.e., with arbitrary poses, facial expressions, occlusions, illumination conditions and motion blur. To overcome difficulties from individual frames, a novel Bayesian formulation is proposed to estimate the posterior probability of a face trait at a specific time, conditional...
We introduce a mobile system for creating high-resolution panoramic images. The user can rotate the camera around an arbitrary axis to create a 2D sweep and see a miniature preview panorama in real-time. The system tracks camera motion and automatically captures high-resolution images and generates a high-quality wide-view panoramic image. We employ a coarse-to-fine method for high-quality registration,...
Structured Light is a well-known method for acquiring 3D surface data. Single-shot methods are restricted to the use of only one pattern, but make it possible to measure even moving objects with simple and compact hardware setups. However, they typically operate at lower resolutions and are less robust than multi-shot approaches. This paper presents an algorithm for decoding images of a scene illuminated...
Image encoding using interest points is a common technique in computer vision. In this paper we present a scale and rotation invariant shape centered interest point (SCIP) detector. By means of detecting singularities in Gradient Vector Flow (GVF) fields we find points of high symmetry in the image. Due to the nature of the underlying GVF field we can employ our features to group together edge-based...
This paper presents a novel approach for matching 2D points between a video projector and a digital camera. Our method is motivated by camera-projector applications for which the projected image needs to be warped to prevent geometric distortion. Since the warping process often needs geometric information on the 3D scene that can only be obtained from triangulation, we propose a technique for matching...
Intestinal motility analysis is an important examination in detection of various intestinal malfunctions. One of the big challenges of automatic motility analysis is how to compare sequence of images and extract dynamic paterns taking into account the high deformability of the intestine wall as well as the capsule motion. From clinical point of view the ability to align endoluminal scene sequences...
We propose an alternative to univariate statistics for identifying population differences in functional connectivity. Our feature selection method is based on a procedure that searches across subsets of the data to isolate a set of robust, predictive functional connections. The metric, known as the Gini Importance, also summarizes multivariate patterns of interaction, which cannot be captured by univariate...
For on-line learning algorithms, which are applied in many vision tasks such as detection or tracking, robust integration of unlabeled samples is a crucial point. Various strategies such as self-training, semi-supervised learning and multiple-instance learning have been proposed. However, these methods are either too adaptive, which causes drifting, or biased by a prior, which hinders incorporation...
In this paper we present a new robust method for recognizing face images using a robust tensorial representation of binary gaussian jet maps (Tensor-Jet). This tensorial representation captures local appearance while retaining information about the spatial structure. During the tensors construction, each Gaussian Jet map is calculated with a Half Octave Gaussian Pyramid using a linear complexity algorithm...
Computer vision-based interfaces to games hold the promise of rich natural interaction and thus a more realistic gaming experience. Therefore, the video games industry started to develop and market computer vision-based games recently with great success. Due to limited computational resources, they employ mostly simple algorithms such as background subtraction, instead of sophisticated motion estimation...
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