collision detection – A problem regarding 2D ray casting

I wanted to post this on stack overflow, but I feel that this SE is more appropriate.

I am extremely naive in the world of ray casting technology so I’m trying to create one out of my own knowledge about how it works. Currently, I have a 2D raycaster that solves a bunch of linear equations to look for collisions of rays and shapes; my shapes are defined by a set of linear equations.

However, the lines that make up a shape are independent of one another and therefore the ray casts “through” the object and detects a collision on its far interior side. I want my program to remove these sorts of detections somehow. Any suggestions?

Again, I’m new raycasting and programming in general, so any level of help is much appreciated!

collision detection – Best option to narrow a known set of triangles?

I am building collision detection and response in a custom engine. This routine happens between the moving player, and static entities on the map.

In the first phase, the broad phase I am moving the player and looking for any new AABB to AABB collisions between the player and static entities.

In the second phase, the narrow phase. I then do a swept-spehere to triangle detection. I move the players collision sphere through the triangles in the colliding AABB.This phase can be expensive because the colliding AABB may have complicated geometry with many triangles.

I ways to narrow down the set of triangles being detected. Some solutions I have in mind are:

  • Get the “overlap box” the space where both AABB’s overlap in the broad phase.

    Then do a pass on all the triangles in the colliding AABB and return just the ones in the overlap box.
    My understanding here is I’ll have to use a SAT algorithm to detect if the AABB and triangles collide or not and I’ll still have to iterate over all the triangles in the colliding AABB. I’m not sure if this is any more performant.

  • Sort the triangles by distance to the AABB collision

    If I sort the triangles by their distance to the AABB collision I will be able to exit from the narrow phase before the entire set of triangles has been processed.
    I’m not sure what the performance implications of resorting the triangles each frame would be. I’m thinking not great…

  • Use a spatial partitioning data structure OctTree or quadTree to narrow down the triangles.

    It may be extensive work to build one of these structures together for my engine and populate it with all the entities triangles. I’m not sure if they will give me any improved granularity. Will they be more precise than the AABB overlap?

I wanted to ask for help first before I start building one these solutions and reviewing the performance. Any other ideas are greatly appreciated.

20.04 – USB detection problem!

I have the Ubuntu 20.04 LTS 64-bit OS.
My problem is that the system does not recognize or detect my USB, I looked in the disk manager but there was no entry or access to it, but what it does detect in the USB port is the mouse. Could you tell me what the problem will be?

collision detection – Game Maker – Raycasting from camera in orthographic projection

I have been trying to figure out how to click on 3D objects in Game Maker Studio 2. I am using an orthographic projection.

I know the basic idea is to calculate a ray that comes from the camera through the screen at the cursor position. But I don’t really know how to calculate that ray, and what I can find online looks like it assumes a perspective projection rather than orthographic.

I know the position of the camera, but I guess I don’t know where the “screen” is relative to the camera position.

Change detection for & # 39; Docker-compose build & # 39; in ansible

Let's say an ansible task is done docker-compose pulland report the result like this:

changed_when: "'... pull complete' in result.stderr |default('')"

That works because stdout shows "… pull complete" only the first time; if the image exists, it does not exist.

Is there a similar way of dealing with docker-compose build?

Whether you are building an image for the first time, or if it already exists, stdout always shows me:

Successfully built fbd38aa5b45a
Successfully tagged foo / bar: last

I also marked "$?" which is always 0. Is there any way to detect if the compilation occurred or not?

PE static detection

I am currently doing a static analysis of the PE file. I have some little questions.

 Can PE file have two or more executable sections? 
    How can we detect whether it is inject or not?

data structure: how to handle grid-based collision detection when an entity spans multiple cells in the grid?

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resolution: objective definition of the parameters necessary for facial detection, recognition and identification in digital images

Are there peer-reviewed studies looking at the effects of pixel density on a person's ability to identify, recognize, and detect human (specifically facial) subjects?

I've searched several sources, but it only seems to find results that address image resolution and the effectiveness of face detection software.

Collision detection of "rounded" tiles from Super Mario Bros

I am working on a Mario bros clone with SDL and C ++ (for educational purposes only / and for fun)
I got collision detection by using AABB collision detection and solving one axis at a time:

  1. Check the collision with the X axis first
  2. Move entity if no collision is detected
  3. Check the collision with the Y axis.
  4. Move entity if no collision is detected

This works great!
However, one thing I really like about the original Mario Bros is that the tiles have a kind of "rounded" feel. I think this helps the map feel more organic, see how Mario moves to the left by jumping into a corner in the original SNES game:

enter the image description here

I thought about using a circular collider for Mario instead of an AABB.
This would cause Mario to "fall" off the tiles if you get too close to the edges. But maybe someone knows a better approach. I have been thinking about collision detection longer than I would like to admit.
I would love to know if anyone has a clean approach to achieve what the GIF shows.

resolution: objective definition of the parameters for facial detection, recognition and identification in digital images

Axis Communications has provided guidelines on the operational requirements of a camera to identify, recognize, and detect human subjects (https://www.axis.com/en-ca/learning/web-articles/perfect-pixel-count/pixel- density ).
They cited the Swedish National Laboratory for Forensic Sciences and the International Standard IEC 62676-4 in explanation of their recommendations, however I cannot find these specific texts.

Are there peer-reviewed studies looking at the effects of pixel density on a person's ability to identify, recognize, and detect human (specifically facial) subjects?

I've searched several sources, but it only seems to find results that address image resolution and the effectiveness of face detection software.