Xuezhi Yue, Ye Fan, Yuan Zeng, Weitao Fan, Luhui Zhou
{"title":"基于混合边框的改进型人体模型快速碰撞检测算法","authors":"Xuezhi Yue, Ye Fan, Yuan Zeng, Weitao Fan, Luhui Zhou","doi":"10.4018/ijcini.345655","DOIUrl":null,"url":null,"abstract":"This article analyzes the commonly used collision detection methods in game engines and designs a hybrid bounding box structure that is more suitable for human models based on their motion characteristics. In addition, this article also optimized the collision response algorithm after the system detects collisions, making the collision response process faster. Through experimental analysis, this approach has a good effect in addressing the problem of model penetration caused by continuously changing the model posture in shooting games; it also avoids the game fairness problem caused by model penetration and improves the realism of the game's virtual environment.","PeriodicalId":509295,"journal":{"name":"International Journal of Cognitive Informatics and Natural Intelligence","volume":" 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Improved Fast Collision Detection Algorithm for Human Models Based on Hybrid Bounding Boxes\",\"authors\":\"Xuezhi Yue, Ye Fan, Yuan Zeng, Weitao Fan, Luhui Zhou\",\"doi\":\"10.4018/ijcini.345655\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article analyzes the commonly used collision detection methods in game engines and designs a hybrid bounding box structure that is more suitable for human models based on their motion characteristics. In addition, this article also optimized the collision response algorithm after the system detects collisions, making the collision response process faster. Through experimental analysis, this approach has a good effect in addressing the problem of model penetration caused by continuously changing the model posture in shooting games; it also avoids the game fairness problem caused by model penetration and improves the realism of the game's virtual environment.\",\"PeriodicalId\":509295,\"journal\":{\"name\":\"International Journal of Cognitive Informatics and Natural Intelligence\",\"volume\":\" 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Cognitive Informatics and Natural Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijcini.345655\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Cognitive Informatics and Natural Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijcini.345655","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Fast Collision Detection Algorithm for Human Models Based on Hybrid Bounding Boxes
This article analyzes the commonly used collision detection methods in game engines and designs a hybrid bounding box structure that is more suitable for human models based on their motion characteristics. In addition, this article also optimized the collision response algorithm after the system detects collisions, making the collision response process faster. Through experimental analysis, this approach has a good effect in addressing the problem of model penetration caused by continuously changing the model posture in shooting games; it also avoids the game fairness problem caused by model penetration and improves the realism of the game's virtual environment.