A. Freeman, L. Cain, Holly Zelnio, Edward Watson, O. Mendoza-Schrock
{"title":"小区域运动图像(MAMI)下马塔数据挑战问题","authors":"A. Freeman, L. Cain, Holly Zelnio, Edward Watson, O. Mendoza-Schrock","doi":"10.1109/NAECON.2014.7045806","DOIUrl":null,"url":null,"abstract":"The ability to classify a dismount and its activity, is of interest for both military and non-military applications. This effort describes a database that is rich for dismount activity classification and is available to the public - the Minor Area Motion Imagery Dismount Tower Data (MAMI-DTD) Collection. The MAMI-DTD collection was gathered in the Summer of 2013 and contains several examples of dismount activity such as running, walking, walking with a load, etc. It is unique because it contains a variety of operating conditions including angular diversity. Furthermore, it contains multi-modal data - infared (IR), passive visible, etc. This paper provides a detailed description of the data collection and details some interesting challenges such as gender, activity, and hierarchical classification.","PeriodicalId":318539,"journal":{"name":"NAECON 2014 - IEEE National Aerospace and Electronics Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Minor Area Motion Imagery (MAMI) Dismount Tower Data challenge problems\",\"authors\":\"A. Freeman, L. Cain, Holly Zelnio, Edward Watson, O. Mendoza-Schrock\",\"doi\":\"10.1109/NAECON.2014.7045806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ability to classify a dismount and its activity, is of interest for both military and non-military applications. This effort describes a database that is rich for dismount activity classification and is available to the public - the Minor Area Motion Imagery Dismount Tower Data (MAMI-DTD) Collection. The MAMI-DTD collection was gathered in the Summer of 2013 and contains several examples of dismount activity such as running, walking, walking with a load, etc. It is unique because it contains a variety of operating conditions including angular diversity. Furthermore, it contains multi-modal data - infared (IR), passive visible, etc. This paper provides a detailed description of the data collection and details some interesting challenges such as gender, activity, and hierarchical classification.\",\"PeriodicalId\":318539,\"journal\":{\"name\":\"NAECON 2014 - IEEE National Aerospace and Electronics Conference\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NAECON 2014 - IEEE National Aerospace and Electronics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAECON.2014.7045806\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAECON 2014 - IEEE National Aerospace and Electronics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON.2014.7045806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Minor Area Motion Imagery (MAMI) Dismount Tower Data challenge problems
The ability to classify a dismount and its activity, is of interest for both military and non-military applications. This effort describes a database that is rich for dismount activity classification and is available to the public - the Minor Area Motion Imagery Dismount Tower Data (MAMI-DTD) Collection. The MAMI-DTD collection was gathered in the Summer of 2013 and contains several examples of dismount activity such as running, walking, walking with a load, etc. It is unique because it contains a variety of operating conditions including angular diversity. Furthermore, it contains multi-modal data - infared (IR), passive visible, etc. This paper provides a detailed description of the data collection and details some interesting challenges such as gender, activity, and hierarchical classification.