From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

We propose a generalized equation to represent a continuum of surface reconstruction solutions of a given non-integrable gradient field. We show that common approaches such as Poisson solver and Frankot-Chellappa algorithm are special cases of this generalized equation. For a N x N pixel grid, the subspace of all integrable gradient fields is of dimension N 2 - 1. Our framework can be applied to derive a range of meaningful surface reconstructions from this high dimensional space. The key observation is that the range of solutions is related to the degree of anisotropy in applying weights to the gradients in the integration process. While common approaches use isotropic weights, we show that by using a progression of spatially varying anisotropic weights, we can achieve significant improvement in reconstructions. We propose (a) α-surfaces using binary weights, where the parameter a allows trade off between smoothness and robustness, (b) M-estimators and edge preserving regularization using continuous weights and (c) Diffusion using affine transformation of gradients. We provide results on photometric stereo, compare with previous approaches and show that anisotropic treatment discounts noise while recovering salient features in reconstructions.

What Is the Range of Surface Reconstructions from a Gradient Field

A method and system for modeling and processing vehicular traffic data and information, comprising: (a) transforming a spatial representation of a road network into a network of spatially interdependent and interrelated oriented road sections, for forming an oriented road section network; (b) acquiring a variety of the vehicular traffic data and information associated with the oriented road section network, from a variety of sources; (c) prioritizing, filtering, and controlling, the vehicular traffic data and information acquired from each of the variety of sources; (d) calculating a mean normalized travel time (NTT) value for each oriented road section of said oriented road section network using the prioritized, filtered, and controlled, vehicular traffic data and information associated with each source, for forming a partial current vehicular traffic situation picture associated with each source; (e) fusing the partial current traffic situation picture associated with each source, for generating a single complete current vehicular traffic situation picture associated with entire oriented road section network; (f) predicting a future complete vehicular traffic situation picture associated with the entire oriented road section network; and (g) using the current vehicular traffic situation picture and the future vehicular traffic situation picture for providing a variety of vehicular traffic related service applications to end users.

Method and system for modeling and processing vehicular traffic data and information and applying thereof

Apparatus, systems, and methods are provided for substantially continuous biometric identification (CBID) of an individual using eye signals in real time. The apparatus is included within a wearable computing device with identification of the device wearer based on iris recognition within one or more cameras directed at one or both eyes, and/or other physiological, anatomical and/or behavioral measures. Verification of device user identity can be used to enable or disable the display of secure information. Identity verification can also be included within information that is transmitted from the device in order to determine appropriate security measures by remote processing units. The apparatus may be incorporated within wearable computing that performs other functions including vision correction, head-mounted display, viewing the surrounding environment using scene camera(s), recording audio data via a microphone, and/or other sensing equipment.

Systems and methods for discerning eye signals and continuous biometric identification

A sequence of biometric data images is received, such as, for example, a sequence of fingerprint images, and a set of biometric data images is selected from the sequence of images. The set of images can include one or more segments of at least one image in the sequence of images. One or more portions of at least one image of biometric data in the set of images can be selected to be included in the unified image of biometric data. The unified image of biometric data can be constructed using the one or more portions of the at least one image of biometric data. If the unified image of biometric data is not complete, a user can be prompted for one or more additional images of biometric data.

Fingerprint Sensing and Enrollment

A system and method for inpainting areas in a fingerprint image is provided. The method includes the steps of dividing a fingerprint image into a plurality of image blocks (506) and computing a plurality of block scores for the plurality of image blocks (508). The method also includes generating a blur matrix for the fingerprint image based on the plurality of block scores (510). The method further includes deriving an inpaint region (IR) matrix for the fingerprint image based on a weighting function and the blur matrix, the IR matrix identifying a portion of the plurality of image blocks for inpainting (512, 514).

Automatic identification of fingerprint inpainting target areas

A computer system (60) for processing interferometric synthetic aperture radar (SAR) images includes a database for storing SAR images to be processed, and a processor (69) for processing interferometric SAR images from the database. The processing includes receiving first and second complex SAR data sets of a same scene, with the second complex SAR data set being offset in phase with respect to the first complex SAR data set. Each complex SAR data set includes a plurality of pixels. An interferogram is formed based on the first and second complex SAR data sets for providing a phase difference therebetween. A complex anisotropic diffusion algorithm is applied to the interferogram. The interferogram includes a real and an imaginary part for each pixel. A shock filter is applied to the interferogram. The processing further includes performing a two-dimensional variational phase unwrapping on the interferogram after application of the shock filter.

Method and apparatus for processing complex interferometric SAR data

A computer system for processing synthetic aperture radar (SAR) images includes a database for storing SAR images to be processed, and a processor for processing a SAR image from the database. The processing includes determining noise in a SAR image to be processed, selecting a noise threshold for the SAR image based on the determined noise, and mathematically adjusting an anisotropic diffusion algorithm based on the selected noise threshold. The adjusted anisotropic diffusion algorithm is applied to the SAR image.

Method and apparatus for processing sar images based on an anisotropic diffusion filtering algorithm

Systems and methods for secure communications in a communications network ( 100 ), including a server ( 102 ) and a client device ( 104 a, 104 b ), are provided. A method includes transmitting a communications session request from the client device to the server ( 304 ), the session request including an in-situ biometric code associated with a biometric sample of a user. The method also includes separately comparing at the server and the client device the in-situ biometric code and an associated canonical biometric code based on comparison criterion ( 208, 310 ), the canonical biometric code representing a biometric reference for the user. The method also includes generating an encryption key at the server and at the client device based on the in-situ and canonical biometric codes ( 218, 314 ). The method further includes establishing an encrypted communications session between the server and the client device if the in-situ biometric code meets comparison criteria at the server and at client device ( 220, 316 ).

Secure digital communications via biometric key generation

A geospatial modeling system (50') may include a geospatial model data storage device (51') and a processor (52') cooperating with the geospatial model data storage device for inpainting seam-smoothed, void-fill data into a void (221') in a geospatial data set (220') for a geospatial region. The processor (52') may select raw void-fill data from the geospatial data set (200'), and generate the seam-smoothed, void-fill data by applying Poisson's equation to the raw void-fill data using boundary conditions based upon data along a corresponding interface between the void region and adjacent portions of the geospatial region.

Josef Allen

Papers

Automatic identification of fingerprint inpainting target areas

Method and apparatus for processing complex interferometric SAR data

Method and apparatus for processing sar images based on an anisotropic diffusion filtering algorithm

Secure digital communications via biometric key generation

Geospatial modeling system providing poisson-based void inpainting and related methods