Midterm Progress

Concept:

 

I thought of two main ideas when thinking of making a game, and to highlight  the previous themes of randomness I decided to make a gambling-oriented game. The first idea I thought of was to make a blackjack game but with Russian roulette stakes. The second idea was to just simulate a Russian roulette. I continued with the latter game because it is more intuitive and the game would be more feasible to implement in p5.js.

 

Design:

 

I drew a basic sketch due to simply show the gameplay features where the level progresses based on the health of the person interacting with the game. If it is feasible, I will also implement another health bar for the dealer, where the player can shoot the dealer as well. I am focusing on the gameplay elements more than the artwork, since the backdrop is intentionally designed to be gloomy and dark. (The filling in of the sketches also represents a vast darkness obscuring the dealer’s torso).

 

The lighting portrayed will also be minimal, and the dealer’s face is drawn in a way where the dealer is wearing a mask that obscures his facial features (essentially like a uniform nearly fully garment that wraps around his entire face, making the facial features appear opaque). I will improve the sketch and render the artwork in SVG.

 

 

Challenges:

The main challenges are producing the artwork with the goal of making the experience as fun as possible, as I might have to compromise on certain gameplay features. I also faced challenges creating the artwork in a correct SVG format, but I am continuing to research this in order to be able to finalize my methods in sketching and digitalizing the artwork. Another challenge is the animations, and to solve this challenge I will focus on 4-5 main animations, one where the dealer shoots a bullet, one where the dealer loads the gun away from the player’s perspective, and one where the dealer shoots a blank.

 

Reading Response:

 

Computer Vision differs from human vision in the sense that the processing of images and light is sub-consciously performed in human vision. On the other hand, algorithms allow computer vision to map light and images into mathematical equivalents in real-time within programs, subsequently allowing the image to be processed.

 

One such method is frame differencing, two frames are taken, where one frame represents a certain amount of light and a representation of the image in pixels, and the second frame represents a corresponding frame with changes in light and pixels. The differences , namely in color and luminosity, between these two frames is summed across all of the pixels’ locations. Similarly, detecting presence performs these same calculations of differences but with a reference of the background of the image instead of two similar frames.

 

I believe that computer vision’s capacity for tracking and surveillance creates possibilities with no bounds, where interactive artwork can take form through the medium of augmented reality, as well as the depiction of interactive media artwork simulating motion and pictures with life-like movement. As highlighted in the reading, this capacity is not limited by definition of the generalizability of computer vision algorithms, where no single algorithm is generalizable, and several different possible algorithms can work in harmony to create a digital interactive artwork.