Month: September 2024

Week 5 – Reading Reflection

After reading Computer Vision for Artists and Designers, I found myself reflecting on how this technology has made its way from industrial and military applications to creative fields like interactive art. One of the points that struck me is how accessible computer vision techniques have become, allowing artists and designers to explore new creative possibilities. It made me think about the similarities and differences between how humans and computers perceive the world. While human vision is complex, combining perception, intuition, and context, computers break down visual input into patterns, often missing the nuances that we take for granted. For example, when we see someone waving, we instantly understand the context — whether it’s a friendly greeting or an attempt to get attention, using cues like their expression and the setting. In contrast, computer vision algorithms like frame differencing detect only the motion of the hand, missing the gesture’s meaning. This shows us how computers rely on measurable inputs, while human vision combines objective information with subjective interpretation.

When it comes to helping computers track what we’re interested in, I think optimizing the physical environment plays a crucial role. The article discusses techniques like proper lighting and camera placement, which seem necessary for improving accuracy. These considerations remind me that even though we can program computers to “see,” there’s still a lot of fine-tuning involved to get the desired results. The tools mentioned, such as Processing and Max/MSP/Jitter, also seem promising for artists who may not have deep programming knowledge but want to experiment with computer vision.

I believe computer vision’s ability to track and surveil raises important questions about its use in interactive art. It offers exciting possibilities, such as creating responsive environments or immersive installations. However, it also introduces concerns about privacy and surveillance, especially when this technology is used outside artistic contexts. In interactive art, it can feel playful and creative, but the same technology in everyday spaces could feel invasive. This duality makes me wonder if we need to establish boundaries around how this technology is used, both for art and for broader societal purposes.

reading response | week 5

The reading explains how computer vision, originally used in military and law enforcement, is now accessible to artists and designers. It discusses the challenges of making computer vision work effectively and suggests tools to help artists use it in their projects. Computer vision and human vision differ in a few ways. Human vision relies on the brain’s ability to understand complex scenes, recognize patterns, and adapt quickly, while computer vision is a set of algorithms that extracts data from digital images. Human vision is intuitive, recognizing objects in various lighting conditions and angles. Computers, however, require explicit programming to process pixels and identify patterns. While human eyes focus on the most relevant parts of a scene, computers process images as data without any true understanding of what they’re “seeing.” Human visual perception isn’t fully understood, so computer vision isn’t perfect.

In interactive art, computer vision allows artists to track movements and respond to viewers in real-time, making the experience more engaging and interactive. But because it can also be used for surveillance, it raises questions about privacy and control. This mix of being both creative and intrusive becomes a double edged sword.

Reading Reflection – Week 5

Exploring the Pioneering World of Videoplace and Computer Vision

One of the most intriguing things about technology before the 2010s is how companies like Videoplace managed to harness ‘Artificial Reality’ between 1969 and 1975. This was long before smartphones and personal computers became mainstream, making their achievements feel ahead of their time. In fact, Videoplace was a pioneer in creating a VR-like experience, and this early attempt at computer vision offers us a glimpse into how computers and humans “see” differently.

Computer Vision vs. Human Vision

While human vision is holistic and context-driven, computer vision is all about analyzing images pixel by pixel. For example, Myron Krueger’s Videoplace used algorithms like the brightest pixel detection to track users’ movements. This means the computer focused on changes in brightness and motion, rather than understanding the full scene as a human would. Despite this difference, computers excel at tracking minute details or movements that humans might miss, making them ideal for tasks requiring precision.

Techniques for Helping Computers “See”

The article discusses techniques like motion detection, which helps computers identify changes in pixel values to track movement. These early algorithms now form the foundation of modern visual effects software like Adobe After Effects and Nuke, allowing them to “see” and track objects with high accuracy. As someone interested in filmmaking, I’ve realized how powerful this technology is for enhancing video quality and adding visual effects, making it possible to create dynamic, interactive experiences.

The Impact on Interactive Art and Surveillance

Videoplace demonstrated how computer vision can transform interactive art, allowing viewers to influence digital experiences in real-time. This ability to track movements made art installations more immersive, blending the boundaries between the physical and digital world. However, this same technology also lends itself to surveillance, as seen with systems like the Suicide Box, which monitored human behavior. This dual nature of computer vision—both as an artistic tool and a means of surveillance—reveals its vast potential and challenges in shaping interactive media. This shows how interactive media is not just limited to entertainment but also social political issues within society.

Final Thoughts 

Reflecting on Krueger’s belief that human interaction is vital in developing computer systems, it’s clear that his vision holds true today. Despite their differences, computer vision and human vision can work together to create compelling, interactive experiences. Understanding how to leverage this technology allows us to not just create art but to redefine how we engage with the digital world. It’s fascinating to realize that the more we harness computer vision, the more limitless our creative potential becomes.

 

Sources Used
  • http://www.flong.com/archive/texts/essays/essay_cvad/index.html (The article
  • Grammarly and ChatGPT  for grammar and paragraph formatting.

Reading Reflection – Week 5

I found this article “Computer Vision” to be quite fascinating, especially when the author talked about how computer vision technologies used to be limited to military and law-enforcement purposes, when it is now also used for programming and creative purposes. Computer vision holds a significant position in creating ideas and designs for areas such as novel artworks, games, and home automation systems. I really liked how this article showed a lot of examples of whatever the author was talking about, such as the first interactive artwork to incorporate computer vision and elementary computer vision techniques, while also showing visual examples of the concept. This really helped me understand the idea and see how it would play out in real life. I also really enjoyed how much I learned in quite a little amount of content compared to our other readings, which I’ll talk about later.

Some of the ways in which computer vision differs from human vision as stated in the article is “generalization,” where computer vision algorithms are not fully general as they are highly dependent on assumptions about the real-world video scene. On the other hand, humans are easily able to adapt and generalize what they’re seeing across a bigger range of contexts. Another difference is computers’ vs humans’ abilities to differentiate and infer what they’re seeing if the subjects are too similar in color or brightness. Computer vision struggles to work well if there isn’t a significant contrast between people and the environments, meanwhile humans are able to tell people and things apart, even if the brightness and color of the backgrounds are very similar. These made me think of how easy it is for us to determine what things are. We’re very lucky to be able to process these things so quickly, because not only would it harm us in terms of survival, it would also harm us in terms of social life. Imagine your friend sees you and waves at you, only for you to not be able to process or see them because they’re unintentionally matching with the wall. It would be embarrassing for them and complicated for you. It also helps that we can generalize enough to be able to tell that our friends are our friends instead of processing them as a newly discovered bug just because they decided to wear a new bright color palette of clothes one day.

One more difference that is also a technique humans can use to help the computer see is by using infrared. Infrared is invisible to the human eye, but helps improve the signal-to-noise ratio of video that’s capture in low-light conditions. This helps computer vision operate in near to complete darkness, something that humans can’t quite do. Another technique is the use of retroreflective marking materials, which helps ensure high-contrast video of tracked objects due to the light illuminating and reflecting back. Reading on this unintentionally reminded me of and answered a question I forgot I had back when I was a kid in elementary school. When crossing the street to get to school, I always wondered why the crossing guards wore bright yellow or orange jackets with silver stripes. This answered why. The high-contrast brightness and reflectiveness is to enhance their visibility, especially in dark conditions, by illuminating light back to the drivers.

Before reading this article, I would think that when it comes to interactive art, computer vision’s ability to track would allow for direct engagement with the artist and/or the audience. It enables immediate user feedback from viewers’ actions, such as Myron Krueger’s “Videoplace,” which analyzed participants’ silhouettes and movements to create graphical responses in real-time based on their interactions. These real-time interactions and visual responses are able to enhance the experience and make it more immersive and engaging. I thought that it would just be for good interactive fun. But after reading this, I realized how many issues could rise from it. It could end up being problematic, like Bureau of Inverse Technology’s “Suicide Box,” which has led to controversy over the ethics of recording suicides and if the suicides are even real. Even with the bad and good, it could also be used in a negative light to help shed light and raise awareness. David Rokeby’s “Sorting Daemon,” inspired by concerns over surveillance and profiling, uses computer vision to survey the environment and extract and sort people in his piece as a way to question the ethics of using technology for reasons such as profiling. I didn’t realize how complex the uses of computer vision could get, but now I’ve seen several perspectives on how it could be viewed as fun, beneficial, or problematic.

Overall, this was a really good read and I learned a lot more than I expected from it. I thought I would just learn what computer vision is and a couple of examples of how it works and how it could be implemented into interactive art, but I ended up learning way more than that

Week 5 – Reading Response

One fundamental difference between human and computer is that computer cannot easily distinguish between objects. They only recognize sources as pixels and algorithms have to be implemented to distinguish a specific object. What impressed me most in the reading is Myron Krueger’s Videoplay. The system he built has a diverse enough reaction bank that users can play with. Based on the movement of the participants, the computer generates visual cues accordingly to that input. Based on the participants’ actions, the computer generates visual cues accordingly. I think the ability to respond flexibly gives the system an impression of intellectual thinking, rather than just following rigid algorithms. I also noticed how Krueger interpreted physical interaction in human-computer interaction. For example, squeezing a virtual character on the screen causes it to pop and disappear (4:12), making the interaction between human and computer feel more realistic and reducing the sense of untouchability of objects on the screen.

Other techniques that I find interesting to be used in interactive design are detecting presence and simple interactions described by Jonah Warren. Because the way computer is used in daily life is mostly rigid and only tailored to specific needs, tweaking computer’s reaction based on the aforementioned input can create an interesting art media. For example, the Cheese Installation by Christian Möller is a unique way of interpreting computer data. Normally, we would not perceive the intensity of a smile in specific percentage. However, the way the machine interprets how we smile and return it into visual cue create a creative material for artwork. As such, a simple footage of smiling can be turned into a scrutiny of someone’s emotions.

Reading Reflection – Week 5

Computer vision is an extremely interesting concept, and emerging technologies significantly boost its development. Although the author mentioned that machines were not capable of doing ‘generalized’ visual input analysis and were heavily dependent on the specific set of programming techniques that would allow them to recognize only certain real-world scenes, I believe that soon (if not already), thanks to the rapid growth of AI, computers will be able to receive and process the information in a ‘general’ way without the need for the special setup in the software. Still, such a technology will probably not be widely applied at the beginning. In one of the Core classes that I recently took, we were talking a lot about Machine Learning, and one of the techniques that are used in that field with the purpose of computer vision enhancement is the Convolutional Neural Network, or CNN which learns by filtering the inputs of text, images and even sounds. Other techniques that were mentioned in the reading include brightness adjustment threshold, background subtraction, and frame differencing. All of them are described to be used to help a computer recognize the visual patterns and track changes in them, but I am sure that now there certainly exist some highly advanced technologies that, although probably based on the techniques described by the author, but still work much more efficiently and maybe incorporate a number of other methods simultaneously.

The development of computer vision is obviously a large step in our technological and scientific progress. It can be used for a lot of good things aimed at improving our lives. In healthcare, for example, it can be used to help doctors diagnose and treat patients or even assist them during surgeries. It is also widely used in self-driving vehicles, which can potentially improve road traveling conditions by making them much more regulated and safer. Computer vision can also be used for leisure activities and entertainment like games – I remember playing Xbox 360 with Kinect, a device that could track your motions and allow you to play some very cool games where you actually needed to jump and do some physical activities in real life, and they would affect the actions of your character in the game. As for Interactive Art, a great example of computer vision implementation is the installation that we recently saw in class, where you can catch the letters with your arms.

However, by implementing all these advanced technologies like motion and face recognition, we should always keep in mind the potential ethical issues that can arise as the line between interaction and privacy becomes more and more blurred. Not to mention, surveillance devices can also raise concerns among people as they become more and more ubiquitous and use high-level precision that is trained by analyzing hundreds of thousands of patterns of human facial expression, emotional behavior, etc. There are many questions that put in doubt the legitimacy of the development of such technologies as human rights can be at stake, but I guess such a discussion can last for a very long time. In my opinion, we just need to keep in mind that each of us can have different perspectives and attitudes toward computer vision, and this is completely normal.

Week 2 Assignment: Rotating Optical Illusion

Concept

I was influenced by the optical illusions that I encountered during my childhood. Consequently, I resolved to develop something similar. The code uses the way motion, shape, and color interact with each other to make a dynamic visual experience that looks like an optical illusion.

Optical illusions use the way our brains handle patterns, color changes, and movement to make us feel things like depth, movement, or distortion that aren’t really there.

The squares’s lineup here make it look like the image is spinning and pulsing in the opposite direction when the user “pauses” the rotating effect by pressing the “Space” button because the speed of the movement changes abruptly. The slowly changing colors and the many concentric squares’ borders also mess with how we think about depth, drawing our attention inward while the colors in the background change easily, throwing us off.

Sketch

Code I am proud of

“For()” loops are very important to this sketch because they let you make grids of circular squares over and over again. The ‘for()’ loops make placing each square easier by going through different places over and over again. Without them, it would be hard to do by hand. The design of these loops is both organized and complicated, which improves the illusion itself.

// Loop for centers of every possible square patterns
for (let x = -500 + 50; x < 500; x += 100) {
  for (let y = -500 + 50; y < 500; y += 100) {
    // Variable stroke color based on a sine wave
    changeCol = sin(t * 100);
    let newCol = map(changeCol, -1, 1, 0, 255);

    // Draw multiple concentric squares with decreasing sizes and random RGB values
    stroke(newCol);
    strokeWeight(3);
    fill(r, g, b, 60); // Random RGB with fixed alpha
    rect(x, y, 80, 80);

    stroke(newCol / 2);
    fill(r, g, b, 80); // RGB for smaller square
    rect(x, y, 60, 60);

    stroke(newCol / 4);
    fill(r, g, b, 120); // RGB for even smaller square
    rect(x, y, 40, 40);

    stroke(newCol / 6);
    fill(r, g, b, 140); // RGB with different alpha
    rect(x, y, 20, 20);

    stroke(newCol / 8);
    fill(r, g, b, 160); // RGB with a different alpha
    rect(x, y, 10, 10);
  }
}

These loops also make the sketch scalable and easy to edit in the future.

Future Improvements

  • There should be a live control panel with settings for things like spinning speed, background color transition speed, and square size. This would give people more control over the illusion and let them make the experience their own.
  • Adding a z-axis or moving based on depth would make things even more complicated. The sense of 3D space could be better created by making the squares bigger in the center and smaller in the background to show depth.
  • Random colors add variety, but a color pattern that works well together can make something look better.

Reading Response – Week 5

This week’s reading was very interesting as it dives into the technicalities of computer vision, making it seem a lot more doable, than what one might think. By breaking down computer vision into its algorithm’s basic fundamental nature, it becomes something as simple as is this pixel’s brightness greater than or less than my threshold value. Although this type of algorithmic analysis is completely different from how we as humans use vision to understand the world, it does seem like an interesting idea to conceptualize. The farthest I can reach in comparison between computer vision and human vision (as someone with no visual impairments) might be in looking at a black-and-white photo or viewing something with a stark contrast filter.

These algorithms are super interesting though because we can literally just work from light comparison in order to send different messages to the computer about what it’s seeing. In order to optimize this it is important that we give the computer clear cut distinctions from what we want it to focus on and what we don’t. I also find it interesting how beyond light, we can use things such as heat to act as the eyes of the computer.

I think computer vision’s capacity for tracking and surveillance affects its use in interactive art because opens new avenues for creativity and expression through computers. I think with the term surveillance specifically, it can also significantly reduce an individual’s right to privacy for the sake of “art.” For example, the Suicide Box project, in my opinion is completely unethical and an abuse of ‘public privacy.’ However, that then stems the issue beyond interactive art because it becomes an issue of privacy and security. Nonetheless, because computer vision has a multitude of applications I don’t believe it is at all limited to what it can be used for in interactive art, which is why we need to stay on top of its usage to ensure people’s security.

Week 5 Reading Response: Computer Vision for Artists and Designers

Computer Vision has consistently been a prominent subject among programmers. It is a principal catalyst in the AI sector today, emerging as a viable option in the healthcare business and enhancing security. However, this reading not only provides a historical context to Computer Vision being the cold, technical niche used by military and mainstream industry; it has now become an accesible tool for artists, paving the way for an increased integration between computers and artists. This seems especially applicable in the modern day, when the lines separating engineering and art are becoming increasingly hazy and anyone can create interactive, visually stunning experiences.

The recurring theme in the reading is how artists have used Computer Vision to to build interactive exhibits that engage spectators in real time. Myron Kruger’s “VideoPlace” is a fitting example of this, turning a cold, impersonal technology to something deeply human-centered: using full-body interactions as a dynamic input to create immersive environments. In Computer Engineering, this is closely tied to the evolving user interfaces, which today powers technologies like motion sensors and gesture-based controls in gaming (Like VR).

Regarding the difference between Computer and Human Vision, one important difference between computers and humans is that computers use algorithms to understand images, but human vision is intuitive and contextual. The computer can “see” what “we” want it to by using techniques like frame differencing, background removal, and brightness thresholding, but these approaches are frequently inflexible, periodic and task-specific in contrast to the flexible nature of human vision. Another key difference is the number of input channels in human and computer vision. Humans take multiple inputs like colors, contrast, visual acuity and so on to make a cohesive perception, while computers only take a limited input based on the task they are intended to perform.

In interactive art, this rigidity in Computer Vision can actually be useful as it helps in simplifying the interaction to specific movements or gestures, allowing for a clearer, more focused experience for the viewers. However, as seen in the case of “Sorting Daemon” by David Robesky, such automated systems can profile people, leading to intrusive monitoring and raise other ethical concerns. As Computer Vision technology develops further, it is imperative to guarantee accountability, equity, and transparency in its application.

Week 5: Computer Vision for Artists and Designers

The topic of computer vision has been an increasingly popular idea, and I believe in the next couple years there will continue to be big leaps in its development and applications. To think that less than a decade ago computer vision was solely for the military and for those in higher education has now turn into a readily available technology for artists and the general public is amazing. As such, I really enjoy how the author presented the paper for beginners in computer vision and provided advice on how to approach projects with computer vision. The projects on tracking and surveillance were actually some of the projects that stuck with me the most throughout the reading. The Suicide Box project I felt on one hand sort of telling the story of the individual whom society, especially when their death wasn’t accounted for, but on the other hand super demoralizing because the project relies on the death of these individual. As such, I feel the capacity for tracking and surveillance for computer vision is a sensitive and difficult issue to uncover fully. There is of course a huge capacity and room for growth in the field of computer vision, however the ethnicity needs to be checked and balance with the morality and freedoms of individuals.

Through the reading, the author mentions how computer visions programs will need to be chosen mindful in order to optimally tackle the problem at hand. With complicated terms such as background subtract and frame differencing, I believe the complexity of differentiating between objects, backgrounds, and lighting is the biggest different from computer vision to human vision. As humans, we process millions of tiny information at once without noticing it and as programmers, the little things like recognizing an object are magnified as humans attempt to describe in code what that object is in computer language. Working with interactive media and computer vision for the rest of the semester, I believe the techniques regarding background subtraction and brightness tracking will play the biggest role in our projects. I feel many of our projects will rely on clear differentiating of human movements and interactions with the project. Without these techniques, I fear our projects may fall apart or not work as the screen would act as a camera and not a program which can be interacted with.