{"title":"Open source stack for Structure from Motion 3D reconstruction: A geometric overview","authors":"Djurdjani, Dany Laksono","doi":"10.1109/INAES.2016.7821933","DOIUrl":"https://doi.org/10.1109/INAES.2016.7821933","url":null,"abstract":"Given a series of overlapped images, it is possible to reconstruct camera position and orientation, as well as 3D coordinates of object in the images. Such method is known as Structure from Motion (SfM), which is currently implemented in various commercial and open source software. The first software commonly don't provide Sfm algorithm. While the latter software are commonly developed partially. This research aims to perform a SfM reconstruction using a stack of open source SfM software, with each software serves different purposes in producing 3D models from images. A python script were employed to produce seamless integration of the software. Geometric evaluations were performed to the result of SfM reconstruction on three datasets obtained using mobile handheld camera. The deliverables of the stack were compared to result of commercial software using cloud-to-cloud comparison to obtain geometric closeness of both the results. Ground truth measurement were conducted to assess the positional consistency in SfM reconstruction on different dataset. The test showed that 3D models resulted from the open source stack perform on pair with the result of Agisoft Photoscan as indicated by the small RMSE value obtained from cloud-to-cloud comparison (0.019818 m and 0.350701 m for two datasets, respectively). The result of ground-truth evaluation indicates large error possibly due to the homogeneity in the dataset used, as indicated by the camera pose graph.","PeriodicalId":101856,"journal":{"name":"2016 6th International Annual Engineering Seminar (InAES)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115716656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"2D to 3D space transformation for facial animation based on marker data","authors":"Troy, Pranowo, Samuel Gandang Gunanto","doi":"10.1109/INAES.2016.7821896","DOIUrl":"https://doi.org/10.1109/INAES.2016.7821896","url":null,"abstract":"Computer facial animation aims to create an animated character expression as natural as possible as well as human facial expressions. Using the data marker catches facial motion capture, will be determined the location of the feature points of 3D face models to follow the motion of the marker points of human faces. To overcome the morphological differences between the face of the source with the character's face, then applied with radial basis retargeting process mapping so that the character's face can still display the natural expression. Using the data marker 2D, Radial Basis Function (RBF) transformation was applied to determine the position of the feature points on the 3D face models. RBF space transformation has good ability in determining the appropriate facial motion marker points on a human face to the character's face. Motion that occurs in 3D face models is scaled according to the relative scale between the source and the target.","PeriodicalId":101856,"journal":{"name":"2016 6th International Annual Engineering Seminar (InAES)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127830149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Silvester Kristian Sungkono, B. W. Yohanes, D. Santoso
{"title":"Decision tree analysis for humanoid robot soccer goalkeeper algorithm","authors":"Silvester Kristian Sungkono, B. W. Yohanes, D. Santoso","doi":"10.1109/INAES.2016.7821905","DOIUrl":"https://doi.org/10.1109/INAES.2016.7821905","url":null,"abstract":"Latest humanoid robot soccer competition rule specifies larger field, wider goal line, and more number of robotics available for a team than before. In consequence, the humanoid goalkeeper needs to be more responsive in adjusting its position to follow ball movement and to react precisely to block incoming shots. Both the robotic control system and algorithm have to be refined. In this article, the humanoid goalkeeper algorithm is extended by utilizing compass to help with direction, using inter-robots communication to share information regarding ball location, using head servo orientation to look around, providing vision via Android smartphone camera, and employ landmarks in the field to provide guidance. There are many attributes perceived by robot sensors in preparing robotic motions and strategy. Each attribute is considered as a random event with uncertain values. Here, decision tree analysis based on entropy and information gain are used to evaluate the uncertainty. Overall, there are some improvements for the humanoid goalkeeper performance.","PeriodicalId":101856,"journal":{"name":"2016 6th International Annual Engineering Seminar (InAES)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126987588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Riasetiawan, G. Quirchmayr, E. Neuhold, A. Tjoa, A. Ashari, Irwan Endrayanto
{"title":"Data Center workload performance in dynamic resources allocation","authors":"M. Riasetiawan, G. Quirchmayr, E. Neuhold, A. Tjoa, A. Ashari, Irwan Endrayanto","doi":"10.1109/INAES.2016.7821904","DOIUrl":"https://doi.org/10.1109/INAES.2016.7821904","url":null,"abstract":"The resource allocation is an essential aspect of Data Center performance. The strategy between dynamic and dedicated resource allocation have objectives in performance and reliability. The performance consists of workload, usage, and processing performance. The study works in workload performance test in dynamic resource allocation. The research present the correlation between load handling memory usage impacted the performance index. The relation between the aspect gives the behavior and characteristics in the workload performance. The result can be used for a baseline to identify and manage the resource management and reach the reliable performance of Data Center.","PeriodicalId":101856,"journal":{"name":"2016 6th International Annual Engineering Seminar (InAES)","volume":"769 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113986472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}