Kenan Bektaş

A testbed combining visual perception models for geographic gaze contingent displays

We present a testbed featuring gaze-contingent displays (GCDs), in which we combined multiple models of the human visual system (HVS) to manage the visual level of detail. GCDs respond to the viewer’s gaze in real-time, rendering a space-variant visualization. Our testbed is optimized for testing mathematical models of the human visual perception utilized in GCDs. Specifically, we combined models of contrast sensitivity, color perception and depth of field; and customized our implementation for geographic imagery. In this customization process, similarly to the geographic information systems (GIS), we georeference the input images, add vector layers on demand, and enable stereo viewing. After the implementation, we studied the computational and perceptual benefits of the studied perceptual models in terms of data reduction and user experience in geographic information science (GIScience) domain. Our computational validation experiments and the user study results indicate the HVS-based data reduction solutions are competitive, and encourage further research. We believe the research outcome and the testbed will be relevant in domains where visual interpretation of imagery is a part of professional life; such as in search and rescue, damage assessment in hazards, geographic image interpretation or urban planning.

Survey of True 3D and Raster Level of Detail Support in GIS Software

Principles of stereoscopic vision have long been used in geographic data processing and visualization. In recent years, a number of mainstream digital devices and systems with stereoscopic capabilities are marketed to public, making True 3D visualizations more accessible. This trend may potentially impact how spatial data is visualized in everyday life. In low-bandwidth environments, however, level of detail (LOD) management approaches have to be applied for efficient processing of large -True 3D-spatial datasets. In order to outline future research needs in True 3D visualizations, this paper presents a survey on current support provided in common Geographic Information Systems (GIS). The survey is designed to document whether the visualization modules of the selected systems a) can display 3D b) can display stereoscopic 3D c) can manage different levels of detail when displaying raster graphics. We document the names of visualization modules and report the types of stereoscopic operations, stereoscopic viewing methods and raster LOD management approaches in surveyed software. The analysis shows that all surveyed GIS support non-stereoscopic or stereoscopic 3D visualizations and a form of raster LOD management. Present raster LOD techniques in the surveyed systems are efficient for level switching when scale changes, however, unlike in other graphics processing software, none of them utilize human visual system inspired approaches. We hope that findings from this study will allow both researchers and practitioners to assess the current state of True 3D and raster LOD management support in widely used GIS software.

Measured and perceived visual complexity: a comparative study among three online map providers

ABSTRACT We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use.

Combining Human Visual System Models for Geographic Gaze Contingent Displays

We present a gaze-contingent display (GCD) in which we combine multiple models of the human visual system (HVS) to manage the visual level of detail (LOD). GCDs respond to the viewer’s gaze in real time, rendering a space-variant visualization. We aim to measure the computational and perceptual benefits of the proposed HVS models in terms of data reduction and user experience. Specifically, we combine models of contrast sensitivity, color perception and depth of field; and customize our implementation for geographic imagery. We believe this research is relevant in all domains that use image interpretation.