Category: Reading03

This article made me think about human gait recognition and its use as a a means for biometric identification. This led me to stumble across this paper on free-view gait recognition which is an attempt to solve the problem of gait recognition needing to have multiple views to be effectively measured/identified, and the use of multiple cameras in city-wide security systems to build such identification. So this combination of using security systems and then deploying algorithmic identification to make the specificity of human beings by the ways in which they move through such surveillance systems seems like an act of “nonhuman” photography that arises out of the combination of smaller systems of “nonhuman” photography.  So I am interested in what other collisions of “nonhuman” systems of photography can intersect with each other to create unintended image portraits.

“Nonhuman photography can allow us to unsee ourselves from our parochial human-centered anchoring, and encourage a different vision of both ourselves and what we call the world.” I think that the above example concerned with gait identification is about trying to see something specific, and I am interested in the fragments and detritus that could be created from this (and other systems of collision). For example, in the picture below one can see the images compiled and the lines they create for the gait detection to be accurate, but this for me raises an aesthetic question of what does the imagery needed to identify people via their gate look like. What are the human portraits created out of surveillance and algorithmic identification?

One example of a human-nonhuman process that Zylinska talks about is the search for dark matter. I had very recently attended a lecture describing the locating of possible dark matter, something that leaves a gravitational imprint but cannot be detected via any other known method. Scientist use advanced telescope and other advanced astronomical measurements, (that I unfortunately did not catch) to view an immensely detailed view of a snippet of the universe. By using the human eye, we can look at galaxy shapes and other patterns in galaxy formation to hypothesize the where about of dark matter. Then trading it back off to the computer for finer details in terms of the actual amount and the coordinates of the possible whereabouts. This process of non-human to human to non-human then back again to human filters through the visual information that is deemed unnecessary to hone in on the invisible.

Reading this article made me recall the candid Machinery Lecture, and the collection of weird images taken from Google Earth I think it was. Even though the images were captured by a satellite, a human still needs to go through the stills to pick out the ones that indicate some strange phenomena. The camera itself, isn’t able to distinguish between normal and strange behavior, even though it still has the agency to “take photo’s”. I think my big takeaway when it comes to photography based on algorithms and computational methods is that it still needs a conscious human brain to make sense of the images and prescribe significance to them. I don’t think I could say that the relationship between the user and the camera could ever be separated completely.

As discussed in the reading, photograms (silhouette images made using light-sensitive paper) are a form of nonhuman photography. Bruce Conner, a pop/abject/assemblage artist active in the ’60s-’80s, made a series of photograms called Angels capturing the human figure in unfamiliar, ghostly poses. Due to the scattering of light, parts of the body that were closer to the capture surface left a brighter mark, making it look like the figures were glowing or emitting superhuman power. Despite the human subjects, the title (literally a divine being) and technique make this work nonhuman.

Zylinska writes that postphotography helps us see the medium as “an assemblage of ‘surface-marking technologies'” rather than a “semiotic/indexical understanding of images.” This wording was familiar to me from more traditional art classes where we were taught to think about 2D art as ‘imagemaking’ rather than separating out categories like drawing, painting, and such which can be constrictive.

I agree with Zylinska that computational and algorithmic techniques are not changing photography fundamentally, rather, they are “intensifying [the nonhuman] condition”. Computation has expanded the field and is helping make complex photographic techniques more accessible. It’s true that computing has enabled three-dimensional, generative, and extrasensory imaging, but at the highest level these practices have existed for a long time (ex. if you conceive of Sol LeWitt’s instructional wall drawings as generative.)

While not necessarily an example of non-human photography as described in the chapter exactly, I think these satellite photos of planes are particularly interesting. They reveal the way that the image is created from red, green, and blue bands that are layered together. Each image is taken by the satellite sequentially, so there’s a slight delay between each. For things on the ground that are relatively still, this is fine, but for fast moving objects like planes each of the frames doesn’t exactly line up. This creates a kind of rainbow shadow. It reveals something about the process that can’t be found in other forms of visible light photography. It’s only possible because of the computational process behind how the images are captured, and is in a sense a kind of a glitch, but a very nice one. Clearly, the author’s observation is correct in that the algorithmic approach intensifies the “nonhuman entanglement,” in addition to revealing something new.

There’s a full album of these planes on Flickr.