Com Arts 155 1st Edition Lecture 7Outline of Last Lecture I. Art Cinema Storytelling and Classical StorytellingII. Transmedia StorytellingOutline of Current Lecture I. Computer LanguagesII. Digital Technology FundamentalsIII. Film versus Digital CaptureIV. Computer GraphicsV. Clarification of Course ContentCurrent LectureComputer Languages Hierarchy of Computer Languages User’s Software Experience Most abstracted. Very far removed from machine language but we’re still speaking through series of systems. Higher Higher Languages (PHB, BASIC) Scripting languages, very much removed form machine languages. They’re really handy for automating any number of tasks, but they don’t give you as much control. Higher Level, Object Oriented Languages (Java) Intermediate Language (C) It’s easy to reuse the same things over and over again; these things are like small programs that we refer to as objects. This is called object-oriented language. This makes things faster to code but we give up some control. Assembly Language Takes a lot of lines of code to do things  Machine Language (1010001 1 100010) It’s really just in 1s and 0s. It’s really hard to read and therefore way easier to make areasDigital Technology FundamentalsThese notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute. 19th Century Digital Inventions It’s not all electronic.  They have a “Difference Engine” and “Analytical Engine” Idea was to create a machine that would let you convert information into numeric symbols and then convert it back again. This allowed you to solve really complex problems.  “Since Babbage’s machine was not electrical, and since all digital computers are in a sense equivalent... the feature of using electricity is thus seen to be only a very superficial similarity.” – Alan Turing, 1950 Basically, there is a lot more to digital technology than electricity. It has fundamentals. Digital Technology’s Real Fundamentals Store information Execute operations Manage the order of operations Convert information into a symbolic, numeric expression After operations are complete, covert it back again with no information loss Ex. Bringing a picture from a camera to Photoshop There is no quality loss as you duplicate it A codec is a program for encoding and decoding data streams Make something into a symbolic sequence and then redo it Example is AVCHD: We will use this in video assignments  20th Century Breakthroughs Transistor (late 1940s) Started to use transistors and semiconductors that could hold either a positive or negative electron. Silicon worked really well with that Microprocessor 1970s- Has 10 of thousands transistors in it. - By putting transistors closer together, with the electrons closer together, it moves faster There are many different ways to manipulate data and each way is going to give you a different level of controlDifferences between Film and digital Film: A Photochemical Process Light comes through lenses and then hits a film and leaves an image on it.  Digital Capture: From Lens to Imaging Senor to Codec Still have lenses. Instead of hitting strip of film, light hits an image sensor. Codec changes that information to an imageComputer Graphics Two forms of Compression Lossless Algorithm packs data in a way that original can be reconstructed. More efficiently maps sequences of data.- It goes through different ways to reconstruct data and tries to find a more efficient way  Run-length encoding: ‘EEEHHH’ becomes ‘E4H3’- You’re cutting down the size of characters. At the end you can fully unpack it again and it’s the same. Efficient way to pack up but can take back out. Examples: Zip, PNG Lossy Algorithm packs data but also throws away data that are considered less important (e.g. sounds beyond the range humans usually hear or minor color variations in a photo)- It throws away data that it considers unimportant. Examples in sound files. Human hearing typically spans about 20 thousand hertz. So if something is really high in that range, this algorithm will throw it out. Another example is a file type like JPEG. It makes images really small by eliminating data.  Example: JPEG, MP3, MPEG4 Nearly all video codecs, including AVCHD, are lossy- We would need tons of server stacks and hard drives if we were trying to capture all the information Computer Graphics Vector Mathematical; Can get scaled up or down without losing clarity  Bitmap: Thinking in Pixels A pixel is the smallest unit that makes up an image on a computer screen, display, or television monitor Shorthand for “picture element”  Pixel Density/ Resolution The more pixels you can fit in an area, the higher the resolution Example: IPhone 3 versus 4 Pixel Density Longtime Mac monitor resolution: 72 PPI Retina display resolution: 220 PPI Minimum PPl for hi-res image printing: 300 PPI- Poster needs to be at this level HD Video Resolution The more pixels, the higher the resolution Why does this all matter? It matters because you’re making decisions all the time that involve this information. Understanding “AVCHD 1080 p 30” AVCHD is codec 1080 is resolution: number of pictures P is progressive  They used to not give you the full image at one time, but rather interlaced pieces of images. However, now it’s progressive. All information all the time 30 is frames per secondClarification of Class Content Photoshop We’ll learn more about Photoshop the more we use it Purpose of lights 3 lights: Key light: primary source of light Fill: gets rid of shadow Backlight: to define objects from background High Key: when the 3 point set up is used in a way to define figures in space without having too much shadow Low Key: We’ve taken away the fill Amps=Watts/Voltage Always try to look at circuit box. Have access to it.  Make sure you’re not plugging in too much into one circuit.  Amps=15 Volts=100 Midterm Thursday, March 5 Two Parts: Multiple Choice and Problem Solving Essay Essay is problem solving orientated. Not going to be asked to analyze a sequence from film. Example: you show up on set. Here’s what the set is like. What are you going