Orientation (computer vision)

About: Orientation (computer vision) is a research topic. Over the lifetime, 17196 publications have been published within this topic receiving 358181 citations.

A computational model for face location

Abstract: The authors adopted a model-based approach, where the shape of the object is defined in terms of several mini-templates. The mini-templates are abstract descriptions of simple geometric features like arcs and corners. Relationships between mini-templates are not rigid. Rather, they are represented by springs that allow deformation of a template in terms of its size and orientation. Cost functionals are determined empirically. The authors expect their system to generate candidate regions in a given photograph associated with a rank of its goodness. >

Real-Time Gaze Estimator Based on Driver's Head Orientation for Forward Collision Warning System

Abstract: This paper presents a vision-based real-time gaze zone estimator based on a driver's head orientation composed of yaw and pitch. Generally, vision-based methods are vulnerable to the wearing of eyeglasses and image variations between day and night. The proposed method is novel in the following four ways: First, the proposed method can work under both day and night conditions and is robust to facial image variation caused by eyeglasses because it only requires simple facial features and not specific features such as eyes, lip corners, and facial contours. Second, an ellipsoidal face model is proposed instead of a cylindrical face model to exactly determine a driver's yaw. Third, we propose new features-the normalized mean and the standard deviation of the horizontal edge projection histogram-to reliably and rapidly estimate a driver's pitch. Fourth, the proposed method obtains an accurate gaze zone by using a support vector machine. Experimental results from 200 000 images showed that the root mean square errors of the estimated yaw and pitch angles are below 7 under both daylight and nighttime conditions. Equivalent results were obtained for drivers with glasses or sunglasses, and 18 gaze zones were accurately estimated using the proposed gaze estimation method.

Curved-Region-Based Ridge Frequency Estimation and Curved Gabor Filters for Fingerprint Image Enhancement

Abstract: Gabor filters (GFs) play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved GFs that locally adapt their shape to the direction of flow. These curved GFs enable the choice of filter parameters that increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved GFs are applied to the curved ridge and valley structures of low-quality fingerprint images. First, we combine two orientation-field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation. Subsequently, these curved regions are used for estimating the local ridge frequency. Finally, curved GFs are defined based on curved regions, and they apply the previously estimated orientations and ridge frequencies for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison with state-of-the-art enhancement methods.

Fast Anisotropic Gauss Filtering

Abstract: We derive the decomposition of the anisotropic Gaussian in a one dimensional Gauss filter in the x-direction followed by a one dimensional filter in a non-orthogonal direction ?. So also the anisotropic Gaussian can be decomposed by dimension. This appears to be extremely efficient from a computing perspective. An implementation scheme for normal convolution and for recursive filtering is proposed. Also directed derivative filters are demonstrated.For the recursive implementation, filtering an 512 × 512 image is performed within 65 msec, independent of the standard deviations and orientation of the filter. Accuracy of the filters is still reasonable when compared to truncation error or recursive approximation error.The anisotropic Gaussian filtering method allows fast calculation of edge and ridge maps, with high spatial and angular accuracy. For tracking applications, the normal anisotropic convolution scheme is more advantageous, with applications in the detection of dashed lines in engineering drawings. The recursive implementation is more attractive in feature detection applications, for instance in affine invariant edge and ridge detection in computer vision. The proposed computational filtering method enables the practical applicability of orientation scale-space analysis.

The perception of surface orientation from multiple sources of optical information

Abstract: One of the fundamental issues in the study of human perception concerns how the shapes of objects in the environment are visually specified from the measurable properties of optical stimulation. There are many different aspects of optical structure that are known to provide perceptually salient information about an object’s threedimensional form. Some of these properties—the socalled pictorial depth cues—are available within individual static images. These include texture gradients, linear perspective, and patterns of shading. Others are defined by the systematic transformations among a sequence of multiple images, and include the disparity between each eye’s view in binocular vision, and the optical deformations that occur when objects are observed in motion. In the theoretical analysis of motion or binocular disparity, two distinct classes of optical phenomena need to be considered. One involves the optical transformations of identifiable image features, such as surface texture or the vertices of a polyhedron, for which it is possible to establish a point-to-point correspondence over multiple views. The ability to match corresponding features in different images is a necessary condition for most existing computational models for the analysis of 3-D shape from motion or stereo, but there are other types of optical transformations that occur frequently in natural vision, for which this condition cannot be satisfied. These include the optical deformations of occlusion contours and smooth gradients of image shading. Patterns of shading in an image arise because of systematic changes in local surface orientation. Patches that are oriented perpendicularly to the prevailing direction of illumination reflect the greatest amount of light, while those that are parallel to the direction of illumination re