I'm a litte confused, because I wanted to create the clone of a 2D game where you ride a tank and your bullets can bounce from the walls, which have irregular shapes (I will paste a link for the example at the end of my post). And now I'm stuck on collision detection for "weird shapes", because I don't know what technique would be the best. I have read about "Bezier curve", "Bresenham algorithm", "pixel perfect collision" and few other, but I still feel that I coplicate this too much and I believe that there must be a simpler solution, but I don't see it. So could you advice me what should I use, if I want to have a ball bouncing from any shape?
Here is the video of the game, which I want to copy:
https://youtu.be/dqDIXLvKfVY
I'm sorry for the quality, my phone isn't there best device for recording videos :P
PS This game is called "action for 2-4 players" - you can search it on youtube if you want a video with better quality. :)
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I'm not very experienced in programming, but I'm building an xG model for an arcade hockey game.
To achieve this, I need to track different actions in the game.
The game has a clock, but statistics from each game do not link statistic (e.g. goal or shot) to a specific time, so I would need to do that first.
I also need to track lots of things from each match, and spit them out into a .xlsx or similar file.
These things include
If a shot is taken, who took the shot, at what time, in what positions (i would use a grid with coordinates system for shooter position)
If a shot is taken, where in the net/goal does it hit, even if its saved
If anybody could point me in the right direction, that would be appreciated.
Sorry if this is the wrong place to ask this question.
I have created a grid and coordinate system based on the game's mini-map, but no code as of yet.
I mean posts per sentence, not per letter. Such a doctor's prescription handwriting which hard to read. Not just a normal handwriting.
In example :
I use a data mining or machine learning for doing a training from
paper handwrited.
User scanning a paper with hard to read writing.
The application doing an image processing.
And the output is some sentence from paper.
And what device to use? (Scanner or webcam)
I am newbie. If could i need some example in vb.net with emguCV/openCV and researches journals.
Any help would be appreciated.
Welcome to stack overflow! The answer to your question is twofold:
a. If you want to recognize handwriting that has already happened i.e. it is presented to you as an image you are in trouble. Computer Vision is still not good enough to provide you with reasonable accuracy.
b. If you have a chance to recognize handwriting “as it's happening” - you are in luck. Download, for example, a Gesture Search app from Android play store and you are in business.
The difference between the two scenarios is subtle but significant. In the second case you have an extra piece of information that makes handwriting recognition possible. This piece is timing of each stroke. In other words, instead of an image with handwriting you have a bunch of strokes that are all labeled with their time stamps. You can think about it as a sequence of lines and curves or as image segmentation - in any way this provides a big hint for the system. Additional help comes from the dictionary on your phone but this is typically used by any handwriting system.
Android of course has an open source library for stroke recognition (find more on your own). If you still want to go for recognizing images though, you have to first detect text (e.g. as a bounding box) and second use any of the existing engines to process detected regions. For text detection I can recommend MSER. But be careful trying to implement even text detection on your own - you are entering a world of pain here ;). Here is an article that can help.
As for learning how to recognize text from images on the Internet - this can be your plan B or C or Z when you master above mentioned stages. Don’t try to abuse learning methods and make them do hard work for you - you will hit a wall if you don’t understand what’s going on under the hood.
Looking to do a proof of concept, and new to Kinect. I believe this is possible, but trying to gauge difficulty with links to tutorials etc explaining how this may work.
Looking to have the Kinect look at a walkway, and essentially detect people movement. This does not mean Skeletal movement, but essentially "foot traffic". I want to determine the noise of traffic, i.e. are there alot of people walking past, or a few. (Note this does not mean counting, just a rough indication. Can this be just pixel movement etc?)
Secondly, if a person then stops and faces the Kinect, pick them up as a user, and track rudimentary movements.
The second part I'm relatively comfortable with, the first I'm not.
Any help is appreciated is pointing me in the right direction. We are a Microsoft house, so any indication if Microsoft SDK, or OpenKinect is the best path would be great too.
I'm wondering, does the Kinect detects joints correctly when it's put on the top (on the ceiling).
I don't have necessary equipment to attach it to ceiling and test, but was wondering whether it reliably detects human. I'm ok even if it confuses the joints, actually.
Has anybody tested this?
From what I've seen while using it, the skeleton detection is iffy from any angle other than directly pointing at a person's front or back. A Kinect pointed straight down with people walking under it would almost certainly not detect anyone, because the human form from above does not look anything like it does from the front. I have had the Kinect pick up random people around me in odd positions (sitting, viewed from the side, etc), but the joints were largely spastic. If you have it mounted on the ceiling and pointed downwards at a sufficient angle to still see people from the front instead of from above.. it could do a fairly good job of picking them up.
So when you say on the ceiling do you mean pointing straight down or still looking at a fairly horizontal angle?
I did a little bit of testing with the Kinect mounted in a very high position (2.5 m, 70° to the ground). As answered by Coeffect it just doesn't work. It doesn't work with Microsoft SDK nor with OpenNI. What I can add is that the skeleton recognition only works if the user is facing the camera with her/his whole body-front. Even worse, both frameworks seem to expect the head at the top of the depth-frame.
Hey, basically i'm on my second App for the iPhone SDK and im really enjoying myself.
Im currently creating a 'raidan' style 2d game, where the user flys a character upward and encounters enemies that shoot bullets etc.
The game is coming along well, I have bullets firing, enemies moving (basic), collecting coins and a fuel/shield system, but i'm starting to become abit overwhelmed with the amount of code and i'm wondering if theres a more 'efficient' way to do this.
I have no layers but for the main layer, for example the HUD is on the same layer as the enemies etc.
If you would use multiple layers, can RectIntersectRect work between layers?
I have also failed to incorporate custom classes, I'm using NSMutableArray's to put all my objects in.
I suppose this is all abit ambiguous.
How would design the architecture for a 2d flight game with multiple levels?
Please understand that I have no clue - I simply started writing methods upon methods upon methods.
Between each level - Would you duplicate methods (physics, UIImageView creation etc)?
Thanks for your thought & time
Georg is right, it’s not easy to give a simple answer to your problems. I would suggest that you spend some time reading the Cocos 2D source code. You will learn some basic tricks that you should do to keep the code manageable. All in all it’s a good idea to use some existing game framework if you are starting. It will keep you from reinventing the wheel and cut down on the design choices.