Picturize

student: Gaganjit Singh landscapes

What is Picturize?                                                                                                            
The Picturize is a tool to represent visual imagery using geo-location information. It serves to provide a collaborative base for visual discussions, information sharing and analysis; reading images captured from various terrestrial and air-borne image capturing devices: cameras, mobile phones, and drones.
What is this for?
Often we visit a place and take a lot of pictures. Sometimes we work in groups/ collaborate as professionals on design research and construction projects. Everyone takes pictures and it often becomes a challenge to organize pictures or to see what someone else saw. Picturize as a tool wants to connect the virtual with the real. It serves to provide as a common platform to instantaneously visualize large picture-sets from various people, irrespective of their sources in three-dimensional space.
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How is this useful?
As a tool Picturize allows to co-relate and understand a place better as a designer being able to connect a virtual 3d mesh representation of a landscape terrain/ a place and personal captured visual imagery. It facilitates this by placing images as view directed picture-frames over a digital terrain model (dtm) in three-dimensional space.
 
Can it do more than just placing and coordinating images?
Picturize facilitates “visual tagging”.The tool also facilitates to give custom names to Pictures you like. Both names and tags, combined with additional image meta-data information like the Latitutde, Longitude, Altitude, FocalLength, and the UserId (the one who took the photograph), can serve as criterion for extended analysis of an Image set. Lexical searches can be performed, and tag-clouds visualized. In addition, location proximity, and region-based searches on an image-set can be performed, which is currently not faciliated by many other image analysis tools. This can help in visually fi ltering a large data set based on navigating a three-dimensional area model. Since the tool reads geo-coordinates stored in images and represents them in three-dimensional space, it also becomes a tool to fi lter images based on a time criterion. So photographs of a place from various times of the year for instance can be inferred and examined very easily. So the need to everytime look and search for images inside multiple nested folders is conveniently avoided by the aid of such a tool. Hence the tool serves as an archival tool.
Picturize also looks to serve as a diagramming tool for image analysis. So based on theself-generated structure of thecaptured imagery, various conclusions can be inferred. Such as, blind-spots in a landscape documentation/ areas of major documentation. This opens to other domains like crowd-sourcing studies, behaviourial patterns and analysis.
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Who does Picturize wish to serve?
Picturize can prove to be an extremely useful tool for various disciplines relying on collection of visual information.Large student groups or offices which keep visiting landscape sites documenting areas of interest can benefit from the time-analysis, visualization and diagramming capacities of the tool.
The tool can be particularly useful for investigating changes visually of an ongoing process in a more stuctured manner than conventional folder-based means of documentation, since based on a time, area/region, and user fi lters one can easily fetch images of the same area and walk-through the changes in an area.
Last but not the least, Picturize is meant for the designer. Additionally developed design tools: “the KarteMaker“ (map overlay tool), and “the FloodSim” (flood simulation tool), allow visual feedback of situations. Picturize tends to bring closer reality and the virtual design processes.
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What is the technology behind these tool?
Picturize is currently written using Python for the Rhino 3d modeling environment, which runs the toolbars. Tools to create data streams from images created from various device are components in Grasshopper (ghPython), utilizing an opensource python module to read image metadata (exif-read).

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