Why do people like cartoons? Options

[*mipadi*]

I stumbled across the most interesting piece of information the other day, which, given the wide interest in graphics on createBlog, I thought might be interesting for users.

Many users here know of the difference between raster images and vector images. For those who are unfamiliar, raster images are ones in which image data (red, green, blue, and alpha [transparency] channels) for each pixel are stored. These images are often described as "photorealistic". PNG's and JPEG's are both raster-based image formats.

Vector images, on the other hand, store geometric and coordinate information for shapes. In other words, a circle is stored as an object with a center, a radius, a fill color, a stroke color, a stroke width, etc. These images are often described as having a "hand-drawn" appearance. Images made in Adobe Illustrator are vector images.

The human eye captures information similarly to a raster image: Light enters the eye and stimulates millions of photo-receptive ("light-sensitive") cells at the back of the eye. In other words, when you see something, you are essentially seeing an image made up of millions of pixels.

But here's the interesting thing: The brain translates this visual input in a way similar to vector images. The brain is much better at breaking down objects in our visual fields into geometric shapes, and simply noting the spatial position (i.e. center), size, color, etc.

So why do humans seem to like cartoons? Cartoons highlight geometric shapes—exactly the way the brain likes to interpret and store imagery. That is why it is easier for the human mind (especially the minds of small children) to process cartoons. Similarly, that is why corporate logos with strong geometric shapes and lines stick in our minds easier.

I found this quite fascinating, which, admittedly, is partly due to my fascination with vector images. It seems so straightforward to store images as a collection of pixels, but it's rather ingenius—not to mention extremely efficient—to break an image down into mathematical calculations. (This is precisely why I find mathematics to be such an exciting and fascinating subject.) I only wonder if the computer scientists who developed vector-based imagery knew that was exactly how our brain retained images!

[*Programmer*]

Intresting...but not all people comprehend geometric shapes as well as others, although the majority might. People retain information in curtain ways and not all the same way. Every brain is unqie in how it processes information. Which is why the brain has always been a complicated thing to study.

I once saw on the discovery channel how twins have similiar brain wave patterns when shown pictures of objects and were asked to discribe what they were. But when compared to someone not related was shown shapes the brain waves were completely different then one of the twins brain waves looking at the same picture.

Futher more i'd like to say that i myself wasn't able to grasp the concept of cartoons till i was at least 7 i've always had problem comprehending geometric shapes.

[Retrogressive]

I came across a website on how modern advertisments use such things to their advantage. I wonder what are some basic examples of this?

[*mipadi*]

There's a lot of advertising with some hard geometric lines and shapes. It's also used a lot in road signs—the stop sign, for example, is a basic geometric shape that is easy to recognize.

[Retrogressive]

McDonalds loves YOU.

[*mipadi*]

There's some pretty nice geometric shapes.

[*Zatanna*]

Great post mipadi (sorry, I don't know your name). My former boss was a neurobiologist. I would talk to her about different things I was doing in Photoshop. We had a great discussion about right and left brains as it relates to vector vs raster images and the way we subconsciously interpret different types of imagery.

Ugh, I wish I could remember the whole conversation, but it was quite a while ago. Maybe when my brain is functioning more I will.

[Retrogressive]

Reasoning functions such as language are often lateralized to the left hemisphere of the brain. Dyscalculia is a neurological syndrome associated with damage to the left temporal-parietal junction[1]. This syndrome is associated with poor number manipulation, poor mental arithmetic, and an inability to understand or apply mathematical concepts[2].

In contrast, visual and music functions such as spatial manipulation, facial perception, and musical ability seem to be lateralized to the right hemisphere.

Other integrative functions such as intuitive or heuristic arithmetic, binaural sound localization, emotions, etc. seem to be more bilaterally controlled[3].

Handedness and language

Broca's area and Wernicke’s area are linked together by a white matter fiber tract called the arcuate fasciculus. This axonal tract allows the neurons between these two brain regions to work together to create vocal language. Further research indicates that, in approximately 98% of right-handed males and 90-95% of right-handed females, language and speech are subserved by the left hemisphere of the brain. Among left-handed people, language is subserved fairly equally by the left, right, or both hemispheres.

There are several methods of determining hemisphere dominance in a living human. The Wada test involves introducing an anesthetic into one hemisphere of the brain through one of the two carotid arteries. Once one hemisphere is anesthetized, a neuropsychological exam is performed to determine dominance for such findings as language production and comprehension, verbal memory, and visual memory. More modern, less invasive, and in some cases costlier techniques, such as functional magnetic resonance imaging and transcranial magnetic stimulation can also be used to determine dominance, but their use is controversial and still considered experimental at most centers.

http://en.wikipedia.org/wiki/Left_brain

Perception and reality

Many cognitive psychologists hold that, as we move about in the world, we create a model of how the world works. That is, we sense the objective world, but our sensations map to percepts, and these percepts are provisional, in the same sense that scientific hypotheses are provisional (cf. in the scientific method). As we acquire new information, our percepts shift. Abraham Pais' biography refers to the 'esemplastic' nature of imagination. In the case of visual perception, some people can actually see the percept shift in their mind's eye. Others who are not picture thinkers, may not necessarily perceive the 'shape-shifting' as their world changes. The 'esemplastic' nature has been shown by experiment: an ambiguous image has multiple interpretations on the perceptual level.

Just as one object can give rise to multiple percepts, so an object may fail to give rise to any percept at all: if the percept has no grounding in a person's experience, the person may literally not perceive it.

This confusing ambiguity of perception is exploited in human technologies such as camouflage, and also in biological mimicry, for example by Peacock butterflies, whose wings bear eye markings that birds respond to as though they were the eyes of a dangerous predator.

Cognitive theories of perception assume there is a poverty of stimulus. This (with reference to perception) is the claim that sensations are, by themselves, unable to provide a unique description of the world. Sensations require 'enriching', which is the role of the mental model. A different type of theory is the perceptual ecology approach of James J. Gibson. Gibson rejected the assumption of a poverty of stimulus by rejecting the notion that perception is based in sensations. Instead, he investigated what information is actually presented to the perceptual systems. He (and the psychologists who work within this paradigm) detailed how the world could be specified to a mobile, exploring organism via the lawful projection of information about the world into energy arrays. Specification is a 1:1 mapping of some aspect of the world into a perceptual array; given such a mapping, no enrichment is required and perception is direct.

http://en.wikipedia.org/wiki/Perception

Pattern recognition is a field within the area of machine learning. Alternatively, it can be defined as "the act of taking in raw data and taking an action based on the category of the data" [1]. As such, it is a collection of methods for supervised learning.

Pattern recognition aims to classify data (patterns) based on either a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space.

A complete pattern recognition system consists of a sensor that gathers the observations to be classified or described; a feature extraction mechanism that computes numeric or symbolic information from the observations; and a classification or description scheme that does the actual job of classifying or describing observations, relying on the extracted features.

The classification or description scheme is usually based on the availability of a set of patterns that have already been classified or described. This set of patterns is termed the training set and the resulting learning strategy is characterised as supervised learning. Learning can also be unsupervised, in the sense that the system is not given an a priori labelling of patterns, instead it establishes the classes itself based on the statistical regularities of the patterns.

The classification or description scheme usually uses one of the following approaches: statistical (or decision theoretic), syntactic (or structural). Statistical pattern recognition is based on statistical characterisations of patterns, assuming that the patterns are generated by a probabilistic system. Structural pattern recognition is based on the structural interrelationships of features.

Typical applications are automatic speech recognition, classification of text into several categories (e.g. spam/non-spam email messages), the automatic recognition of handwritten postal codes on postal envelopes, or the automatic recognition of images of human faces. The last two examples form the subtopic image analysis of pattern recognition that deals with digital images as input to pattern recognition systems.

Pattern recognition is more complex when templates are used to generate variants. For example, in English, sentences often follow the "N-VP" (noun - verb phrase) pattern, but some knowledge of the English language is required to detect the pattern. Pattern recognition is studied in many fields, including psychology, ethology, and computer science.

http://en.wikipedia.org/wiki/Pattern_recognition

blah. I can randomly quote Wikipedia.

[Heathasm]

that is pretty interesting for me too
i pretty much love all vector art <3 i guess i know why now

[EddieV]

Really interesting...

Hmm...

[KissMe2408]

That really is interesting.
Cartoons make me happy too. lol
I mean, c'mon. There is nothing better then after a bad day,
Sitting down on the couch, hot chocolate, and watching an episode of "Ed, Edd, & Eddy". lol it just makes me laugh, and I guess it's so easy to watch. You've been doing it since you were a kid.
Interesting on how it affects your brain and all.
Cartoons are a good thing :)

[technicolour]

^ Ed, Edd, & Eddy is like, awesome.

I like cartoons cause it's something brainless and fun. School sucks, seriously, so like what Katie said, what is better than sitting on the couch and watching a good episode of brainless entertainment? Well, she said the part about the couch thing.

[o0olaalaa]

cartoons make me smilee

[*mipadi*]

cartoons make me smilee

Do they make you smile because they have nice geometry?

[gelionie]

No wonder I found this topic familar... it's because it's from February.

Haha... I really don't want to know exactly how the brain works... too complicated for me.

[Smoogrish]

Wow. This is interesting. I never thought about it that way. I always thought that I enjoyed the content, not the geometric shapes!

[emazing]

Hmm.
Cartoons block out reality [most of the time] with dreams and fantasies, most of which people only want this world to have.

I sound like a self-absorbed nerd, which may not be a bad thing.