Search results
Results from the WOW.Com Content Network
Other features that SDL does have include vector math, collision detection, 2D sprite scene graph management, MIDI support, camera, pixel-array manipulation, transformations, filtering, advanced freetype font support, and drawing. [13] Applications using Pygame can run on Android phones and tablets with the use of Pygame Subset for Android ...
Panda3D is a game engine that includes graphics, audio, I/O, collision detection, and other abilities relevant to the creation of 3D games. [3] Panda3D is free, open-source software under the revised BSD license. Panda3D's intended game-development language is Python.
Collision detection is the computational problem of detecting an intersection of two or more objects in virtual space. More precisely, it deals with the questions of if , when and where two or more objects intersect.
In physical simulations, sweep and prune is a broad phase algorithm used during collision detection to limit the number of pairs of solids that need to be checked for collision, i.e. intersection. This is achieved by sorting the starts (lower bound) and ends (upper bound) of the bounding volume of each solid along a number of arbitrary axes.
Bullet is a physics engine which simulates collision detection as well as soft and rigid body dynamics.It has been used in video games and for visual effects in movies. Erwin Coumans, its main author, won a Scientific and Technical Academy Award [4] for his work on Bullet.
A primary limit of physics engine realism is the approximated result of the constraint resolutions and collision result due to the slow convergence of algorithms. Collision detection computed at a too low frequency can result in objects passing through each other and then being repelled with an abnormal correction force.
"Collision Detection Accelerated: An Optimization Perspective", Montaut, Le Lidec, Petrik, Sivic and Carpentier. This research article notably shows how the original GJK algorithm can be accelerated by exploiting Nesterov-type acceleration strategies, contributing to lowering the overall computational complexity of GJK.
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]