Intelligent model training method and device, and collision detection method and device

Abstract

The invention provides an intelligent model training method and device, a collision detection method and device. The intelligent model training method comprises the steps of obtaining a set of objectsample sets, wherein the set of object samples comprises a plurality of groups of object sample sets and object sample set labels corresponding to each group of object sample sets, each group of object sample sets comprises the size of the object samples, the number of the object samples and the density of the object samples, and each object sample set label comprises a grid layer establishing method; and training an intelligent model through the set of object sample sets to obtain the intelligent model, and enabling the object sample sets to be associated with the object sample set tags through the intelligent model. According to the object sample set, the intelligent model can obtain the corresponding object sample set label, i.e., the grid layer establishment method, so that the time consumption is reduced, and the precision of a collision detection result for subsequently detecting the object sample set is greatly improved.

Description

technical field [0001] The present application relates to the field of Internet technologies, and in particular to an intelligent model training method and device, a collision detection method and device, a computing device and a storage medium. Background technique [0002] At present, collision detection is widely used in different technical fields, such as games, animation production and other technical fields. The most commonly used method in the prior art is to put the detected object into a suitable grid layer for collision detection. Through this grid layer establishment method, the collision detection and detection accuracy of the detected object can be realized. It takes a long time to select a suitable grid layer establishment method from a large number of grid layer establishment methods when creating a grid layer, and the selected grid layer establishment method may not be optimal, which will cause inaccurate collision detection results And collision detection t...

AI Technical Summary

Problems solved by technology

The most commonly used method in the prior art is to put the detected object into a suitable grid layer for collision detection. Through this grid layer establishment method, the collision detection and detection accuracy of the detected object can be realized. It takes a long time to select a suitable grid layer establishment method from a large number of grid layer establishment methods when creating a grid layer, and the selected grid layer establishment method may not be optimal, which will cause inaccurate collision detection results and collision detection takes a long time

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