2016-2017
Recognized / Not Recognized, a comparative movement analysis of popular and unpopular news images
Two channel video installation, 1920 x 1200px, 2m height


The project Recognized / Not Recognized revolves around the question: ‘What features determine ‘successfull’ news photos?’

From a selection of worldwide press agency databases (which include amateur witness photos) I scraped all the news photos in relation to the ten events that received the most coverage in the past five years. This resulted in a database of approx. 850.000 images. By using image recognition software from Google (and some proxies), I determined how many times an individual image exists on the google indexed internet. In other words, the reproduction rate of each image is calculated.

Press photos from a big news event have a wide range of variables but are in a way very uniform - since they are all witness photographs –, therefore my database consists of an ideal set for a cross-sectional study. The analyses of this cross-sectional study finds its way in several visual presentations. This is a photo (taken with Hasselblad)of a typical successfull photo composition.
The video installation places a choreography based on successful images in conjunction with a choreography based on unsuccessful images. All original photographs were taken at the same moment, on the same spot and for the same press agency. By juxtaposing these two series of images, as captured by dancers, they form a parallel choreography in which the dancers move from one frozen position into another position. Each pose is an expression of an actual photograph. The sequences loop as a never-ending study in movement on news photography.

From the enormous sea of photographic data, we tend to choose and therefore find those images that suit our eye and affirm the Western compositional tradition we are surrounded by. The google algorythm is already built on the validation of certain presets and stereotypes. At the moment – with a little bit of effort – unsuccessful photos can still be found behind a login wall. However in the future these images would not even be registrered by the camera, and if the camera delivers them than it is very unlikely they can be retrieved. Unsuccesful news images are then being considered as dirty data and are simply wiped from the system.

Credits:
Choreography: Marjolein Vogels
Dancers: Madelyn Bullard, Chris Guerematchi, Kenzo Kusuda, Patrick Schmatzer, Ilija Surla, Loris Casalino, Pedro Ines, Peter Clark, Loris Casalino, Cherish Menzo
Light: Geek Zwetsloot
Camera: Susanne Bakker
Sound post-processing: Marlon Wolterink

Made possible by: Stimuleringsfonds voor Creatieve Industrie, Stichting MOTI, Museum of the Image, Amsterdam Fonds voor de Kunsten









2016-2017
Recognized / Not Recognized, a comparative movement analysis of popular and unpopular news images
Two channel video installation, 1920 x 1200px, 2m height

The project Recognized / Not Recognized revolves around the question: ‘What features determine ‘successfull’ news photos?’

From a selection of worldwide press agency databases (which include amateur witness photos) I scraped all the news photos in relation to the ten events that received the most coverage in the past five years. This resulted in a database of approx. 850.000 images. By using image recognition software from Google (and some proxies), I determined how many times an individual image exists on the google indexed internet. In other words, the reproduction rate of each image is calculated.

Press photos from a big news event have a wide range of variables but are in a way very uniform - since they are all witness photographs –, therefore my database consists of an ideal set for a cross-sectional study. The analyses of this cross-sectional study finds its way in several visual presentations. This is a photo (taken with Hasselblad)of a typical successfull photo composition.
The video installation places a choreography based on successful images in conjunction with a choreography based on unsuccessful images. All original photographs were taken at the same moment, on the same spot and for the same press agency. By juxtaposing these two series of images, as captured by dancers, they form a parallel choreography in which the dancers move from one frozen position into another position. Each pose is an expression of an actual photograph. The sequences loop as a never-ending study in movement on news photography.

From the enormous sea of photographic data, we tend to choose and therefore find those images that suit our eye and affirm the Western compositional tradition we are surrounded by. The google algorythm is already built on the validation of certain presets and stereotypes. At the moment – with a little bit of effort – unsuccessful photos can still be found behind a login wall. However in the future these images would not even be registrered by the camera, and if the camera delivers them than it is very unlikely they can be retrieved. Unsuccesful news images are then being considered as dirty data and are simply wiped from the system.

Credits:
Choreography: Marjolein Vogels
Dancers: Madelyn Bullard, Chris Guerematchi, Kenzo Kusuda, Patrick Schmatzer, Ilija Surla, Loris Casalino, Pedro Ines, Peter Clark, Loris Casalino, Cherish Menzo
Light: Geek Zwetsloot
Camera: Susanne Bakker
Sound post-processing: Marlon Wolterink

Made possible by: Stimuleringsfonds voor Creatieve Industrie, Stichting MOTI, Museum of the Image, Amsterdam Fonds voor de Kunsten