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Upcoming plans for PPM future.
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[quote="Banshee"][quote="PussyPus"]Be careful of the last keyword of the topic, repliers![/quote] I was expecting that a post like yours would be the real april's fools joke of this topic. What I mean by this is that, surprisingly, [u]the news that I posted above is real[/u]. [quote="G-E"]Well I learned early on that humans "see" contrast, that they need the process of understanding difference to understand the sameness.[/quote] Contrast is used to distinguish different objects in the scene. But note that distinguishing objects and understanding objects are different things. To understand the object, you need to know its frontiers, and contrast is usually what helps people to determine them.[/quote]
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Posted: Thu Apr 06, 2017 11:37 am
that's pretty awesome, Bansh!
Posted: Mon Apr 03, 2017 5:14 am
Well done notifying everyone Banshee! (But it's actually pretty obvious about it being silent here
) anyway, good luck with the doctorate! Hoping to see a better future for PPM
Posted: Sun Apr 02, 2017 8:01 am
I mentioned negation as another method for you to potentially help you define that frontier... I think I more or less understand your process, and it just seems like you might be ignoring the relationship to the nothing
Like the determinism around whether a level change is a slope or a corner can be done both by definition and negation.
Posted: Sun Apr 02, 2017 5:54 am
Be careful of the last keyword of the topic, repliers!
I was expecting that a post like yours would be the real april's fools joke of this topic. What I mean by this is that, surprisingly,
the news that I posted above is real
Well I learned early on that humans "see" contrast, that they need the process of understanding difference to understand the sameness.
Contrast is used to distinguish different objects in the scene. But note that distinguishing objects and understanding objects are different things. To understand the object, you need to know its frontiers, and contrast is usually what helps people to determine them.
Posted: Sat Apr 01, 2017 11:49 pm
Well I learned early on that humans "see" contrast, that they need the process of understanding difference to understand the sameness. The other way to look at this is that we use negation as part of our method to prove something, we prove what it isn't, we categorize what it isn't, and thus help us define what it actually is.
As such, babies are always interested in edges, the point at which something abruptly stops or changes colour, that's where their eyes go, and it is in that point of distinctiveness that they have increased their relative understanding of one side versus the other. The process by which we silly humans focus on contrasts does change over time, we start making assumptions to limit the data we have to process, and our experience helps fill in the parts we can't see, adding another dimension of contrasts. This is also why I was so keen on giving potential modifiers to your modelizer algorithm, to let us discover what we like best, thus add to your body of research while accomplishing something.
People also use the same methodology to define themselves, and identity politics is an offshoot of that, whereas I don't try to define myself at all beyond being aware of my traits or history, a feminist also must define their entire being as an opposition; I am _not_ a subservient woman, I am _not_ going to stay silent, I am _not_ weak etc...
Posted: Sat Apr 01, 2017 11:07 pm
Be careful of the last keyword of the topic, repliers! I love people who are in doctorate.
Posted: Sat Apr 01, 2017 7:49 pm
Post subject: Upcoming plans for PPM future.
Hello everyone! We've been slow on news posting in these recent.... weeks at this site, I am aware of it. We've been relying on your news posts and announcements to keep this place alive. So, if you have something interesting to announce and spread the word, please do it by posting at our
Community News Forum
. But, this doesn't mean the death of this place. I am very passionate about this place and I wouldn't be crazy to just throw it away out of no where.The current situation happens because of a bet for a better future. You know? Sometimes big steps ahead demands big sacrifices.
The current sacrifice is directly related to my doctorate, which I'm having a hard time to finish it. While it is obviously more important for my real life, it will certainly have a great influence at this site as well, mostly at our future modeling tools. Doctorate candidates are obligated to research things that were not covered before, so if you have a plan to make one doctorate, PhD, etc, you should be very careful at revealing your research plans around. It's possible that someone at the other side of the world publish the same thing that you are researching, which may possibly ruin your situation. So, I've been quiet about my research for all these years, at least in the internet. But right now, I'm forced to finish it in a couple of months and, to be very honest, I don't think anyone will be able to finish it in such time, so I can talk a little about it.
As a visual computing scientist, I think it's amusing how most techniques (if not all) applied in my area to handle visual objects or solve problems with it doesn't really know what kind of objects they are dealing with. It's actually kinda ironic, in a certain way. Many of these techniques are based on local approaches. Imagine someone who is blind and deaf at the same time trying to know a place or trying to figure out how to go somewhere. While this person could use their hands and body to know what is around it, he can't know what is going on in the whole scene and use it in his advantage. For you guys at PPM, samples of such approach is the autonormals detection at the
Voxel Section Editor III
, image filters and even the 3D reconstruction techniques in the 3D Modelizer feature of VXLSE III. Other techniques may subdivide the space into smaller parts and treat them as local neighbors. I.e.: Octrees, Wavelets, skeletons and most if not all known hierarquical structures, etc. It's smarter, but you are still influenced by how your object is sampled in first place, which may generate noise in the solution.
You don't need to be acquainted to computer graphics to know that humans doesn't view objects like that, as we pay much more attention to its contents rather than how it is discretized, since there are far too many points for our eyes, isn't it? Objects are subdivided independently of the space metric, but mostly based on our semantic knowledge of them. And that's how we understand objects, languages and any kind of information in the end of the day. And that's what I'm trying to approach with my doctorate research, a graph language that allows me to understand objects and that is far more insensible to noises (bad sampling) than any existing graphic data structure out there.
By understanding objects, we could do a lot of things with them:
- Reconstruct them (zoom in, increase sample resolution, polygonize graphics, etc)
- Parametrize them (so, you can lately add some textures, or you could also use it to compare different objects and move information from one to another)
- Recognize them (and catalog them
without using existing heavy brute force methods
, and then using existing objects to add details to new objects of the kind... or even finding out how to automatically edit certain objects to make them fit into new contexts).
- Distinguish objects and different contexts where they belong, as well as allowing some of them to be auto-completed.
- Pathfinding (it could even be used in RTS games to fix some of the existing pathfinding problems, allow AI to know the best places where to set its defensive buildings or to find the weakest spots of the enemy and send its army in a path where it could exploit it).
It's worth mentioning that I don't have any of these things working at the moment and, in the best of the situations, I may have reconstruction working by the end of my thesis restricted to 2D objects. Coding my proposal is complicated because I have to deal with a bunch of complicated computer graphics and compiler problems at once. And that's what is cracking me so much. But still, this is the first step to
a better understanding of visual objects as we know and a huge set of modeling tools that could make use of it.
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