Photosynths as a method for capturing rich visual, qualitative data8 th International Qualitative Research Conference

6-8 th September

Talbot Campus

Bournemouth University

Gavin D. J. HarperThe ESRC Centre for Business Relationships, Accountability, Sustainability and SocietyCardiff University55 Park PlaceCardiffCF10 3ATUnited Kingdomharpergd@cf.ac.uk

‘Widespread analysis that photographs offer a transparent “window on the world” has discouraged critical analysis of the medium.’

‘The malleability of photographs has injected formerly secure fields with a healthy dose of circumspection’

‘Photographs may not provide us with unbiased objective documentation of the social and material world, but they can show characteristic attributes of people objects and events that often elude even the most skilled wordsmiths.’

The Limitations of Photography

Prosser, Jon., Schwartz, Dona., (1998) Photographs within the sociological research processIn: Prosser (1998) Image-based research: a sourcebook for qualitative researchers

A Picture May Tell A Thousand Words

But How Many Of Those Words Are Fair And True?

Photosynth takes your photos, mashes them together and recreates a 3D scene out of them that anyone can view and move around in.

Different than static photos and video, Photosynth allows you to explore details of places, objects, and events unlike any other media. You can’t stop video, move around and zoom in to check out the smallest details, but with Photosynth you can. And you can’t look at a photo gallery and immediately see the spatial relation between the photos, but with Photosynth you can.

Description taken from http://photosynth.net/about.aspx

What Is ?

The idea was originated by Noah Snavelly at the University of Washington (now at Cornell)

http://www.cs.cornell.edu/~snavely/

His original Ph.D thesis, ‘Phototourism, exploring photo collections in 3D’ http://phototour.cs.washington.edu/

History of

Title of Photosynth

Add Digital PhotosFrom A Folder

Which Appear In This Box

Tags Help Searches

Description

Who can see it

Who can use it

Go!

•Identifying features

•Scalable features

•Matching features across photographs

•Assembly into 3D space

How Does Work?

•Exciting visual method

•Free software

•Works with existing equipment : PC, Digital Camera

Photosynth is a relatively ‘lean’ method of achieving something quite sophisticated; it does not require advanced computation skills from the researcher, yet can be used to achieve something quite complex.

Why Is Photosynth Interesting To Qualitative Researchers?

Data can be ‘triangulated’, by feeding a series of photographs of the same scene into Photosynth, which in turn recreates the spatial relationships between different photographs.

These can be photographs from:

•Different perspectives

•Contrasting views

•Various times and dates

•Dissimilar equipment

•Individual photographers

•Varying ‘levels of detail’

Photosynth as a method of “triangulating” photographic data.

Photosynth allows the creation of a “gestalt” from a diverse range of

photographic source data varying in many different metrics of

appraisal and marked by

dissimilarity

Photosynth can be used to allow qualitative researchers to experience the visual relationship between objects in a space that they haven’t physically visited.

This could be used for example:

•To recreate historical spaces by fusing ‘current’ photographic data with historical photographs in order to create a space that is navigable where data is presented in context.

•To allow the researcher to document and record a given space; providing a model representation using photographic data that is relational or navigable.

•To recreate a space, where there is a temporal dimension to the use of that space that needs to be documented

Photosynth for exploration of space

•Free photosynths must be publicly available; this could present ethics / data handling problems in some forms of research.

•Data must be handled by a third party (Microsoft) this needs to be considered when getting ethical approval as the researcher cannot maintain “full” control of data.

•The data is stored remotely; the “Photosynth” cannot be “downloaded to disk” (but the source files are the record of the data)

Limitations of Photosynth (In it’s present implementation)

No photograph was taken from this viewpoint – yet Photosynth allows me to explore the point cloud in three dimensional space. From this position, you can clearly see the outline, form and shape of the room.

Photosynth data can be mapped onto ‘the world’ by geotagging data.

The interface is relatively sophisticated, as it allows data to be ‘scaled’ in relation to satellite imagery and changed in orientation.

This results in a fine level of detail regarding the orientation and position of pictures.

....maybe in the future it will be possible to record this information when taking the picture (in part it is) and then mine this information during research analysis?

Geospatial Data

Assuming a ‘structuralist’ view of visual data.

Language is a series of “signs” in which words are only arbitrarily tied to visual data. Sassure (1959)

The advantages they confer over a series of pictures is that they allow the ‘linkages’ between photos in a scene to be easily recreated.

A photosynth containing hundreds of millions of pixels of picture information can convey a much greater amount of complexity than a picture with a few million pixels.

Photosynths Can Help Us Make Sense Of The Structure & Complexity In A Scene

David Navon, (1977) Forest before trees; the precedence of global features in visual perceptionIn: Cognitive Psychology, Volume 9, Issue 3, July 1977, Pages 353-383

Perception proceeds from global analysis to more and more fine-grained analysis

The global precedence has a number of possible advantages such as utilization of low-resolution information, economy of processing resources, and disambiguation of indistinct details.

Although evidence from the psychological literature supports the notion that global features are extracted earlier and/or better than local ones, in most previous research little attention has been given to the control over the complexity of global and local features.

Jeffrey Johnson, (2006) Hypernetworks for reconstructing the dynamics of multilevel systemsIn: European Conference on Complex Systems, 25-29 September, Oxford.

R

Arch

Level N

Level N+1 structure

base

R

apex assemblyrelation

Parts aggregate into a wholeThe Fundamental Diagram ofMultilevel Systems

Flower VaseBlue Background

Leaves Stem Thorns

Gold FrameFabric Mountboard

Gold Slip

Framed Picture

North Wall

Dining Room Walls

Bed Warmer

Wooden Handle

BrassWarmer

Representing Some of The Complexity Of The Dining Room Scene•Photosynths allow for the capture of a greater range and depth of visual information than a single picture.•The structural complexity in a Photosynth is much greater than in a single photograph – which could present challenges and opportunities in data analysis.

Level 1

Level 2

Level 4

Level 3

Image Redrawn from:Jeffrey Johnson, (2006) Hypernetworks for reconstructing the dynamics of multilevel systemsIn: European Conference on Complex Systems, 25-29 September, Oxford.

RR1 R2 R1 R2

Features assembled to make a face

Relational cones with a shared base

Relational cones with an intersecting

Photosynth allows us to create a composite view of the world from many photographs taken by others, we can use the ‘social web’ as a source of data...

Experiencing the world through other’s eyes...

•Useful tool for exploring rich qualitative nature.

•Mode of operation is analogous to the way human beings process data, moving from “big picture” to “finer detail”.

•Some data / ethics issues in current implementation, although these could be worked on through changing the user interface – the technology is sound.

•Issues with “crowdsourcing” data from Flickr / Picasa – Privacy / Ethics Issues.

Conclusions

•Useful tool for making sense of “complex visual data”.

•Development of an application protocol interface, and allowing researchers “under the hood” of Photosynth could yield further insight into processing qualitative visual data.

Conclusions

Questions please.

Thank you for listening!