A visual recognition supporting tool for mapping environmental data using handheld measurement instruments

The &#8220;Alpine Environmental Data Analysis Centre&#8221; (AlpEnDAC) is a research data management and analysis platform for research facilities around the Alps and similar mountain ranges. It provides the computational infrastructure for the Virtual Alpine Observatory (VAO), which is a research network of European high-altitude research stations (http://www.vao.bayern.de).&#160;Within the scope of previous work, the platform was developed with the focus on research data and metadata management as well as analysis and simulation tools. It offers the possibility to store and retrieve data securely (data-on-demand), to share it with other scientists and to interpret it with the help of computing-on-demand solutions via a user friendly web-based graphical user interface. The AlpEnDAC allows the analysis and consolidation of heterogeneous data sets from ground-based to satellite instruments.&#160;In a further development phase, launched on 1 August 2019, the existing services of the AlpEnDAC will be supplemented by new components in the fields of user support and quality assurance. Furthermore, the modelling and analysis software portfolio will be extended, focusing on the development of innovative services in the fields of service-on-demand and operating-on-demand as well as the integration of new data sources and measurement instruments.&#160;The AlpEnDAC helps environmental scientists to benefit from modern data management, data analysis, and simulation techniques. The VAO network, now including ten countries (Austria, France, Germany, Georgia, Italy, Norway, Slovenia, Switzerland, Bulgaria, and the Czech Republic) is an ideal and exciting context for developing the AlpEnDAC with researchers.&#160;This project receives funding from the Bavarian State Ministry of the Environment and Consumer Protection.

Download Full-text

Extraction of Building Facades in Urban Space and Texture Mapping to 3D Polygon Map by Using In-Vehicle Camera

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.36.405 ◽

2010 ◽

Vol 36 ◽

pp. 405-412

Author(s):

Hideaki Kawano ◽

Hideaki Orii ◽

Hiroto Kuwano ◽

Tohru Irie ◽

Hiroshi Maeda

Keyword(s):

Urban Space ◽

Texture Mapping ◽

Measurement Instruments ◽

Gps Measurement ◽

Building Facades ◽

Building Area ◽

Building Wall ◽

Supporting Tool ◽

3D Information ◽

Individual Information

Due to the wide diffusion of 3D maps, supporting tool for constructing the 3D maps are required. Individual information necessary for constructing the 3D maps is gathered by some measurement instruments. For example, 3D information and wall textures are acquired by triangulation (or GPS measurement) and optical devices, respectively. Building polygons in a 3D map can be constructed easily by combining the 3D (height) information and a 2D map. It is, however, difficult to obtain an appropriate texture for an arbitrary building polygon by combining those measurements information. In general, the texture mapping with the acquired image is performed manually. However, it takes huge costs to perform in a wide area. Therefore, the demand of the automation is extremely high. In this study, we aim to automatize the texture mapping by image information from the in-vehicle camera. An in-vehicle camera has the advantage that it is possible to take a picture of the building wall while driving over the broad area. But, the vibration and the traffic have influences on the photography environment. As a result, it is difficult to specify the building area in the image. In the proposed method, tracks of the camera are calculated from the acquired continuous image, the building area that corresponds to the polygon on the map is specified. In this paper, we described our observation about the result of a miniature model.

Download Full-text

Do You Want to See the Tree? Ignore the Forest

Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) ◽

10.1027/1618-3169/a000240 ◽

2014 ◽

Vol 61 (3) ◽

pp. 205-214 ◽

Cited By ~ 12

Author(s):

Nicolas Poirel ◽

Claire Sara Krakowski ◽

Sabrina Sayah ◽

Arlette Pineau ◽

Olivier Houdé ◽

...

Keyword(s):

Visual Recognition ◽

Local Level ◽

Local Information ◽

Visual Environment ◽

Global Information ◽

Focus Attention ◽

Global Level ◽

Hierarchical Stimuli ◽

Priming Paradigm ◽

The One

The visual environment consists of global structures (e.g., a forest) made up of local parts (e.g., trees). When compound stimuli are presented (e.g., large global letters composed of arrangements of small local letters), the global unattended information slows responses to local targets. Using a negative priming paradigm, we investigated whether inhibition is required to process hierarchical stimuli when information at the local level is in conflict with the one at the global level. The results show that when local and global information is in conflict, global information must be inhibited to process local information, but that the reverse is not true. This finding has potential direct implications for brain models of visual recognition, by suggesting that when local information is conflicting with global information, inhibitory control reduces feedback activity from global information (e.g., inhibits the forest) which allows the visual system to process local information (e.g., to focus attention on a particular tree).

Download Full-text