In the interactive video installation Selection Method For a Discrete Sequence of Moments I revisit Cartier-Bresson’s decisive moment using computer implemented criteria and algorithms to select the “best” moment from a stream of sequential images. The act of photographing breaks lived experience into discreet moments and video captures many of these discreet moments in succession. These properties allow me to take frames from video and analyze them in order to select a single best moment from all available images. This program does not anticipate the best time to take a photograph, instead it takes many photographs, (30 frames per second for as many seconds as desired) and compares them to each other. Then the program finds the image that contains the most motion, the most faces and the largest faces. These criteria have been chosen to find a moment defined as the height of human induced action. Other criteria can be used to find other moments. This quick computer-aided editing process can help identify which images people want see but it also shows photography to be a medium that can be cracked using brute force methods. Meaning, if we had video of every moment we could find every iconic, decisive photo ever. Of course this is assuming we could create the right computer algorithm to recognize it.
After some examination, I have become frustrated by the idea of a decisive moment because it presupposes a lot about the moments it captures. I am reluctant to say that there is one ultimate split second that is the best moment of an event. Does it mean this photograph is representative can encapsulate an entire experience? We appear to want photographs to stand in for whole events weather they are birthdays, graduations or wars. Cartier-Bresson states that it is a photographers job to understand and anticipate these instants and capture them with a camera. Identification of these moments are apparently intuitive and universal; immediately recognizable and agreed upon by all. Photographers are deemed successful by their ability to tap into an innate talent to find these moments. Perhaps this is an exaggerated interpretation of Cartier-Bresson’s words, but the objective kind of value judgements that this idea introduces do not always seem plausible.
The decisive moment assumes moments we think of as “best” are experienced visually. In this system bombastic events with externalized action are given preference over quiet, inner moments of reflection. This is not so surprising, through out the history of art some of the most prized works have depicted grand scenes of human action orientated towards a viewer, such as History paintings like David’s Oath of the Horatti. However, these moments have requirements to qualify as photographable moments: they need to be lit well, they need to be able to face towards a lens and communicate action clearly. Composition plays a part in creating a successful moment. There needs to be an engaging expression of (preferably) human action, but if it cannot or is not captured in a pleasing way by the camera it will not be decisive. Capturing movement is also important. Photographed subjects can look stationary even while in motion because of position and what we assume movement looks like. In Eadweard Muybridge’s motion studies the image of a horse with all four hoofs off the ground must be in motion because in our experience of the world horses cannot be in the air without being in motion. In an image where only one hoof is raised could be showing a horse in a mid gallop or it could just be lifting its leg while standing. Photographs cannot communicate a difference between these two options. Some photographs show motion to a greater degree than others.
Inspired by these decisive criteria this installation uses custom computer vision software to locate elements like degree and areas of movement as well as size and location of faces. As viewers walk through the installation space they are recorded via a web-cam. The camera is connected to a computer running the custom software that analyzes video footage to find the image with the most movement and faces in it. A monitor displays the selected images. The software can be set to capture and analyze as many frames as desired, although it is usually set to 30 seconds or 900 frames. One best video frame is selected every 30 seconds. This gives viewers time to move around in front of the camera and see their chosen image quickly enough to try new actions in time for the next selection. The selected image appears on the left side of the monitor until the next is chosen for the following 30 seconds. The right side of the monitor shows the computer vision algorithm for each image. Blue outlines show what pixels in the image have changed from the previous frame, which is how the computer determines motion. The large grey circular dial displays the direction of motion for the entire image while the smaller dials show the direction of localized motion. The cyan rectangles are drawn around areas of local motion and green rectangles are drawn around faces. Different algorithms can be set to find different moments. The best portrait might include the least movement and one large face. Information about the algorithms used is also included in the installation as a poster sized scientific abstract that explains the criteria complete with references. Other elements in the installation are variable and depend on the space available. In past exhibitions I have included printed frames of video that illustrate how the algorithm works, Inkjet prints of previously selected images with their analysis images and printed selected images from the current installation that are updated weekly as highlights. Each of these options encourage viewers to contemplate the act of selecting images and encourages them to move around the installation space.
Ideally this installation stimulates viewers to ask what makes a “best” photograph, ponder what kind of images they want to look at and what influences those desires. I think a Cartier-Bresson exhibition could be complemented with this installation because it prompts viewers to think about how his legacy has impacted photography today. New digital cameras include facial recognition to ensure subjects are smiling and iPhones have applications that use accelerometers to shoot images when the photographers hand is the steadiest. All of these developments are working toward assisting the capture of out best moments This project also has several Web applications with opportunities for visitors to experience the decisive moment virtually by uploading their own videos or by viewing selected moments from the museum installation and downloading images they appear in. My goal for this project is not to mechanize photography or make photographers obsolete. Instead I want to look at how photography shapes our understanding of experiencing life.