Develop Reference

how to make a rectangle sprite stick to one side in Unity?

I am using a square sprite in Unity for making Android game. I want this rectangle to be always placed at the bottom of the screen. This strip acts as a ground and other objects can fall on it. I want the lower side of this rectangle to stick to the lower side of the screen. How to do it?.If i try to place it there manually then after I change the screen resolution the placement gets disturbed?Also the camera is not moving, so I only want to fix the position of this strip with respect to the camera once. (i think so). What should i do?

We need a little more information. Sprites at the lower side of the screen, usually intend to be in the UI. Is this the case? If it is, the way to do it is very different from a normal sprite in the world.
(Since I am not allowed to comment, I will try to answer for both cases, however I am not at a computer capable of running Unity, so I can't really provide a concrete answer (aka: Code))
UI:
Add an Image to your Canvas. Go to your anchor preset (inside the Rect Transform) and set it to the appropriate position. Then, in case you want the image to not be stretched, go to the Image component and Check on the "Maintain Aspect Ratio" (Or something like that) option. Add the sprite to the image and you are all set.
World:
Here, the situation is way more complicated. You first need to get the screen dimensions, then calculate the size of the object according to the aspect ratio, then have some Camera.ScreenToWorldPoint conversion and finally use the LookAt method in the Update() in order to have the sprite face the camera at all times. Or use the UI layer as described above, let's be honest that is probably what you need.

Displaying a route on a floor plan image

I have a floor plan on which the walls are black, the doors are orange and the target is red. What I want is to make an app where given a specific point on the image, the route to the target is calculated and displayed. I already have a routing method, but it is in matlab and each position and object is defined in the code and it doesn't use an image. What I would like to know is how to scan the image to identify the walls, the doors and the target by color in order to apply the routing method and then display the route over the image of the map (I guess I should use drawable for that).

This are some steps to implement a pathfinding algorithmm from an image.
Upload your image
Apply a color detection HSV(in the real life is most easy control the
light changes with this format) algorithm to obtain the objects
separately.
Make a new binary Matrix with 1 for your floor and 0 to the
obstacles.
Apply to that binary Matrix an Occupancy grid algorithm(this reduce
your matrix because in the pathfinding algorithm you need
processing).
and now ur path finding algorithm. I recommend use the diijistrak or A star algorithm, in this two cases
you need construct an adjacency matrix.
The graph theory will help you to understand better.Good Luck!!
You can work in processing IDE for rapid prototipyng and migrate all the processing IDE core to eclipse, you need implement the PApplet class in your eclipse project, and can compile your app to Android.

I would use somekind of occupancy grid/map where each grid cell = one pixel (or possibly a small collection of pixels like 2x2 3x3, etc) And just do k-means clustering on the image. There are a few choices for k
k=2
you have walls is one group (the black lines)
everything else is considered opened space (this assumes doors can be opened).
You will need to know where the red point is located, but it doens't need to be visible in your map. It is just another open space in your map. that your program internally knows is the endpoint.
k=4
a group for everything black=walls(occupied), orange=doors(may or may not look like occupied cells depending on whether or not they can be opened),red=target(unoccupied), white=open space(unoccupied).
In both cases you can generate labels for your clusters and use those in your map. I'm not sure what exactly your path finding algorithm is, but typically the goal is to minimize some cost function, and as such you assign a extremely high cost to walls (so they will never be crossed), possibly assign a medium cost to doors (in case they can't be opened). Just some ideas, good luck

Making an ImageView object in android move randomly on the screen

Fairly new at android dev, haven't got any code for this particular step yet so ill try give as much detail as possible. I'm trying to make an ImageView object move around the android view/activity, unlike java im not able to use the random generator to translate it onto an x and or y position on the frame, if anyone could point me on the right direction or more importantly have a good idea on how to do this, that'd be great.

There is a class in android called Random. And there is a function called nextInt() which can give you a random number. You can also calculate the width and height of your screen using DisplayMetrices so that you can keep the image inside the device's screen. And you can also move the ImageView. See this link.

Android: How to detect these objects in images? (Image included). Tried OpenCV and metaioSDK, but both are not working good enough

i have been working with object detection / recognition in images captured from an android device camera recently.
the object i am trying to detect are all kinds of buttons that look like this:
Picture of buttons
so far i have been trying with OpenCV and also with the metaio SDK. results:
OpenCV was always detecting something, but gave lots of false hits. also it is too much work to collect all the pictures for what i have in mind. i have tried three ways with OpenCV:
FeatureDetection (SURF, ORB and so on) -> was way too slow and not enough features on my objects.
Template Matching -> seems to only work when the template is exactly a part out of the scene image
Training classifiers -> this worked the best so far, but is too much work for my goal, and still gives too many false detections.
metaioSDK was working ok when i took my reference images (the icon part of each button) out of a picture like shown above, then printed the full image and pointed my android device camera at the printed picture. but when i tried with the real buttons (not a picture of them) then almost nothing got detected anymore. in the metaio documentation it is said that the reference images need to have lots of features and color differences and also should not only consist of white text. well, as you see my reference images are exactly the opposite from what they should be. but thats just how the buttons look ;)
so, my question would be: does any of you have a suggestion about what else i could try to detect and recognize each of those buttons when i point my android camera at them?

As a suggestion can you try the following approach:
Class-Specific Hough Forest for Object Detection
they provide a C code implementation. Compile and run it and see the results, then replace positive and negative training images with the ones you have according the following rules:
In a car you will need to define the following 3 areas:
target region (the image you provided is a good representation of a target region)
nearby working area (this area have information regarding you target relative location) I would recommend: area 3-5 times the target regions, around the target, can be a good working area
everything outside the above can be used as negative images
then,
Use "many" positive images (100-1000) at different viewing angles (-30 - +30 degrees) and various distances.
You will have to make assumptions at which viewing angles and distances your users will use the application. The more strict they are the better performance you will get. A simple "hint" camera overlay can give a good idea to people what you expect the working area to be.
Use few times (3-5) more different negative image set which includes pictures of things that might be in the camera but should not contribute any target position information.
Do not use big images, somewhere around 100-300px in width should be enough
Assemble the database, and modify the configuration file that the code comes with. Run the program, see if performance is OK for your needs.
The program will return a voting map cloud of the object you are looking fore. Add gaussian blur to it, and apply some threshold to it (you will have to make another assumption for this threshold value).
Extracted mask will define the area you are looking for. The size of the masked region can give you good estimate of the object scale. Given this information it will be much easier to select proper template and perform template matching.
(Also some thoughts) You can also try to do a small trick by using goodFeaturesToTrack function with the mask you got, to get a set of locations and compare them with the corresponding locations on a template. Constuct an SSD and solve it for rotation, scale and transition parameters, by mimizing alignment error (but not sure if this approach will work)

To move an image towards 3 dimensions in android application

I want to move an image in in 3 dimensional way in my android application according to my device movement, for this, I am getting my x y z co-ordinate values through sensorEvent,But I am unable to find APIs to move image in 3 dimesions. Could any one please provide a way(any APIs) to get the solution.

Depending on the particulars of your application, you could consider using OpenGL ES for manipulations in three dimensions. A quite common approach then would be to render the image onto a 'quad' (basically a flat surface consisting of two triangles) and manipulate that using matrices you construct based on the accelerometer data.
An alternative might be to look into extending the standard ImageView, which out of the box supports manipulations by 3x3 matrices. For rotation this will be sufficient, but obviously you will need an extra dimension for translation - which you're probably after, seen your remark about 'moving' an image.
If you decide to go with the first suggestion, this example code should be quite useful to start with. You'll probably be able to plug your sensor data straight into that and simply add the required math for the matrix manipulations.