Faleh Alqahtani, Jasmine Banks, V. Chandran, Jinglan Zhang
{"title":"Three-Dimensional Head Pose Estimation Using a Stereo Camera Arrangement","authors":"Faleh Alqahtani, Jasmine Banks, V. Chandran, Jinglan Zhang","doi":"10.1145/3220511.3220522","DOIUrl":"https://doi.org/10.1145/3220511.3220522","url":null,"abstract":"Head-pose estimation is a crucial component for analysing human behaviour through various 2D and 3D applications. However, the usage of the strategies based on 2D technologies is not very effective, as the sources of data are limited. In contrast, the usage of the strategies based on 3D technologies is a promising area. The 3D HPE methods are also imperfect, especially when they are applied in situations of inconsistent illumination or occlusion. An analysis of related works helps to establish an appropriate framework for the current research, and this paper extends previous work by creating an algorithm that further improves the framework. The method relies upon a stereo camera arrangement and utilises a method to detect and track key landmark points of the human face to evaluate improvement in 3D-head-pose estimation.","PeriodicalId":177319,"journal":{"name":"Proceedings of the International Conference on Machine Vision and Applications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133451004","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":"Emotional and Cognitive Assessment of Use of Functional Animation","authors":"J. Ma, Chun-Ching Chen, Yi-Chun Lin","doi":"10.1145/3220511.3220516","DOIUrl":"https://doi.org/10.1145/3220511.3220516","url":null,"abstract":"The animation transition in the interface can be divided into two parts: functional animation and delightful animation. In past studies, \"function\" and \"emotion\" are often viewed independently. This study is to, with functional transition effect as the research content, investigate whether the cognitive load generated by operation will affect the use of emotions. The author selects 4 experimental samples of animation transition that conform to this study, gets the emotive information in the way of combining the subject's actual operation and subjective questionnaire, and seek the association between cognitive load and emotion, and explore the emotional connection generated in the process of using different types of transitions. The experimental results show that the six faces in the cognitive load will respectively produce unequal connections with pleasure, arousal and dominance at the emotional level, and besides, there will exist emotional and cognitive differences due to different characteristics of animation transition.","PeriodicalId":177319,"journal":{"name":"Proceedings of the International Conference on Machine Vision and Applications","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130234980","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":"Benign and Malignant Solitary Pulmonary Nodules Classification Based on CNN and SVM","authors":"Liu Lu, Y. Liu, Hongyuan Zhao","doi":"10.1145/3220511.3220513","DOIUrl":"https://doi.org/10.1145/3220511.3220513","url":null,"abstract":"In order to assist the doctors to diagnose lung cancer and improve the classification accuracy of benign and malignant pulmonary nodules, this paper proposes a novel intelligent diagnosis model which is aiming at CT imaging features of pulmonary nodules. Specifically, this model uses the convolutional neural network to extract the features of the pulmonary nodules, then uses the principal component analysis to reduce the dimension of the extracted features, and finally classifies the final features with particle swarm optimization optimized SVM. With regard to the pulmonary nodules extracted from the LIDC-IDRI database, 400 pulmonary nodules are used for training and 310 pulmonary nodules are used for testing, the classification accuracy rate is 91.94%. This model can provide objective, convenient and efficient auxiliary method for solving the classification problem of benign and malignant pulmonary nodules in medical images.","PeriodicalId":177319,"journal":{"name":"Proceedings of the International Conference on Machine Vision and Applications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124220623","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":"Saliency-Guide Simplification for Point-Cloud Geometry","authors":"Lixia Wang, Fei Wang, Feng Yan, Yu Guo","doi":"10.1145/3220511.3220523","DOIUrl":"https://doi.org/10.1145/3220511.3220523","url":null,"abstract":"To efficiently simplify large-scale point clouds and keep geometric details as many as possible, we propose a novel operator guided by point-saliency. Firstly, we adopt a site entropy rate algorithm to calculate the saliency value which represents the significance of every point. Intuitively, the point of higher value should be retained. We introduce the saliency value as a weight term to locally optical projection (LOP) operator. What's more, we incorporate locally adaptive density weight into our operator to deal with the highly non-uniformed point clouds. Compared with other methods, our approach preserves more spatial information when down sample a point cloud to a certain number of points. Experimental results also show that our method is highly robust to noise and outliers.","PeriodicalId":177319,"journal":{"name":"Proceedings of the International Conference on Machine Vision and Applications","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128042504","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":"Proceedings of the International Conference on Machine Vision and Applications","authors":"","doi":"10.1145/3220511","DOIUrl":"https://doi.org/10.1145/3220511","url":null,"abstract":"","PeriodicalId":177319,"journal":{"name":"Proceedings of the International Conference on Machine Vision and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125176129","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}