Multi-line Adaptive Perimetry (MAP): A New Procedure for Quantifying Visual Field Integrity for Rapid Assessment of Macular Diseases.

PurposeIn order to monitor visual defects associated with macular degeneration (MD), we present a new psychophysical assessment called multiline adaptive perimetry (MAP) that measures visual field integrity by simultaneously estimating regions associated with perceptual distortions (metamorphopsia) and visual sensitivity loss (scotoma).MethodsWe first ran simulations of MAP with a computerized model of a human observer to determine optimal test design characteristics. In experiment 1, predictions of the model were assessed by simulating metamorphopsia with an eye-tracking device with 20 healthy vision participants. In experiment 2, eight patients (16 eyes) with macular disease completed two MAP assessments separated by about 12 weeks, while a subset (10 eyes) also completed repeated Macular Integrity Assessment (MAIA) microperimetry and Amsler grid exams.ResultsResults revealed strong repeatability of MAP and high accuracy, sensitivity, and specificity (0.89, 0.81, and 0.90, respectively) in classifying patient eyes with severe visual impairment. We also found a significant relationship in terms of the spatial patterns of performance across visual field loci derived from MAP and MAIA microperimetry. However, there was a lack of correspondence between MAP and subjective Amsler grid reports in isolating perceptually distorted regions.ConclusionsThese results highlight the validity and efficacy of MAP in producing quantitative maps of visual field disturbances, including simultaneous mapping of metamorphopsia and sensitivity impairment.Translational relevanceFuture work will be needed to assess applicability of this examination for potential early detection of MD symptoms and/or portable assessment on a home device or computer

FRIOD: a deeply integrated feature-rich interactive system for effective and efficient outlier detection

In this paper, we propose an novel interactive outlier detection system called feature-rich interactive outlier detection (FRIOD), which features a deep integration of human interaction to improve detection performance and greatly streamline the detection process. A user-friendly interactive mechanism is developed to allow easy and intuitive user interaction in all the major stages of the underlying outlier detection algorithm which includes dense cell selection, location-aware distance thresholding, and final top outlier validation. By doing so, we can mitigate the major difficulty of the competitive outlier detection methods in specifying the key parameter values, such as the density and distance thresholds. An innovative optimization approach is also proposed to optimize the grid-based space partitioning, which is a critical step of FRIOD. Such optimization fully considers the high-quality outliers it detects with the aid of human interaction. The experimental evaluation demonstrates that FRIOD can improve the quality of the detected outliers and make the detection process more intuitive, effective, and efficient

Digital Library Services for Three-Dimensional Models

With the growth in computing, storage and networking infrastructure, it is becoming increasingly feasible for multimedia professionals—such as graphic designers in commercial, manufacturing, scientific and entertainment areas—to work with 3D digital models of the objects with which they deal in their domain. Unfortunately most of these models exist in individual repositories, and are not accessible to geographically distributed professionals who are in need of them. Building an efficient digital library system presents a number of challenges. In particular, the following issues need to be addressed: (1) What is the best way of representing 3D models in a digital library, so that the searches can be done faster? (2) How to compress and deliver the 3D models to reduce the storage and bandwidth requirements? (3) How can we represent the user\u27s view on similarity between two objects? (4) What search types can be used to enhance the usability of the digital library and how can we implement these searches, what are the trade-offs? In this research, we have developed a digital library architecture for 3D models that addresses the above issues as well as other technical issues. We have developed a prototype for our 3D digital library (3DLIB) that supports compressed storage, along with retrieval of 3D models. The prototype also supports search and discovery services that are targeted for 3-D models. The key to 3DLIB is a representation of a 3D model that is based on “surface signatures”. This representation captures the shape information of any free-form surface and encodes it into a set of 2D images. We have developed a shape similarity search technique that uses the signature images to compare 3D models. One advantage of the proposed technique is that it works in the compressed domain, thus it eliminates the need for uncompressing in content-based search. Moreover, we have developed an efficient discovery service consisting of a multi-level hierarchical browsing service that enables users to navigate large sets of 3D models. To implement this targeted browsing (find an object that is similar to a given object in a large collection through browsing) we abstract a large set of 3D models to a small set of representative models (key models). The abstraction is based on shape similarity and uses specially tailored clustering techniques. The browsing service applies clustering recursively to limit the number of key models that a user views at any time. We have evaluated the performance of our digital library services using the Princeton Shape Benchmark (PSB) and it shows significantly better precision and recall, as compared to other approaches