{"title":"Evaluation of feature based image stitching algorithm using OpenCV","authors":"Youngmin Ha, Hyun-Deok Kang","doi":"10.1109/HSI.2017.8005034","DOIUrl":"https://doi.org/10.1109/HSI.2017.8005034","url":null,"abstract":"Image stitching is an attractive method to merging multiple images. It can produce a wide-angle panoramic photograph while maintaining the quality of the source images. The process is simply performed by overlapping part of the images which contain common scene. Today, panoramic image stitching is widely used in applications such as 360-degree cameras and virtual reality photography. If the stitching technology ensure fast processing speed and accurate performance, it is expected to produce diverse image contents in real time. Moreover, the panoramic images can be mapped to various projective layouts, e.g. spherical and stereographic projection. The mapping of the panoramic image along the suitable projective layout makes it possible to express more stereoscopic space, that is, the space in the photo can give the impression that it looks as if it is in front. It can be utilized when creating 3D reconstruction space with high-resolution panoramic images. This paper describes the concept of feature based image stitching and presents the implementation results. It also provides the results of stitching with more than 10 images and suggests the time-efficient way for stitching multiple images. The time-efficient stitching method can be applied to various applications so that panoramic images can be easily accessed in everyday life.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129234384","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}
Rajdeep Chatterjee, T. Bandyopadhyay, Debarshi Kumar Sanyal, Dibyajyoti Guha
{"title":"Dimensionality reduction of EEG signal using Fuzzy Discernibility Matrix","authors":"Rajdeep Chatterjee, T. Bandyopadhyay, Debarshi Kumar Sanyal, Dibyajyoti Guha","doi":"10.1109/HSI.2017.8005014","DOIUrl":"https://doi.org/10.1109/HSI.2017.8005014","url":null,"abstract":"High dimensionality of feature space is a problem in supervised machine learning. Redundant or superfluous features either slow down the training process or dilute the quality of classification. Many methods are available in literature for dimensionality reduction. Earlier studies explored a discernibility matrix (DM) based reduct calculation for dimensionality reduction. Discernibility matrix works only on discrete values. But most real-world datasets are continuous in nature. Use of traditional discernibility matrix approach inevitably incurs information loss due to discretization. In this paper, we propose a fuzzified adaptation of discernibility matrix with four variants of dissimilarity measure to deal with continuous data. The proposed algorithm has been applied on EEG dataset-III from BCI competition-II. The reduced dataset is then classified using Support Vector Machine (SVM). The performance of the proposed Fuzzy Discernibility Matrix (FDM) variants are compared with original discernibility matrix based method and Principal Component Analysis (PCA). In our empirical study, the proposed method outperforms the other two methods, thus suggesting that it is competitive with them.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124541241","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":"The acceptance of social network: The role of status seeking on TAM","authors":"Wornchanok Chaiyasoonthorn, Watanyoo Suksa-Ngiam","doi":"10.1109/HSI.2017.8005049","DOIUrl":"https://doi.org/10.1109/HSI.2017.8005049","url":null,"abstract":"online social networks are progressively being adopted among young people in developing countries. The public is questioning why so many people adopt this technology in many aspects of their lives? The purpose of this study is to understand the acceptance of social networks by Thai students. We used traditional TAM's behavioral constructs: subjective norms (SN), perceived usefulness, perceived ease of use (PEOU), and behavioral intention (BI) together with status seeking (SS) to answer the question. We surveyed 350 Thai university students and use structural equation modelling (SEM) for the analysis. The findings depict a significant theoretical model and suggest the future research.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129535783","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":"Sterile zone monitoring with human verification","authors":"Ajmal Shahbaz, Wahyono, K. Jo","doi":"10.1109/HSI.2017.8004997","DOIUrl":"https://doi.org/10.1109/HSI.2017.8004997","url":null,"abstract":"This paper proposes efficient real time method for sterile zone monitoring with human verification. The propose method consists of two main parts: Motion detection module and human verification module. The role of motion detection module is to segment out foreground object from background. Probabilistic Foreground Detector based on Gaussian Mixture Model(GMM) is used. Region of interest (ROI) obtained from motion detection module is fed into SVM classifier. SVM classifier is trained using HOG descriptor. The proposed method is tested on the standard datasets gives promising results.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122361491","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":"Predicting students performance in final examination using linear regression and multilayer perceptron","authors":"Febrianti Widyahastuti, V. U. Tjhin","doi":"10.1109/HSI.2017.8005026","DOIUrl":"https://doi.org/10.1109/HSI.2017.8005026","url":null,"abstract":"Currently, many educational institutions are highly oriented to improve the quality of education and students? learning achievement-examination result. To fulfil such intention, predicting students? performance by analyzing their learning behavior is one of the best way can be taken into account. Once the performance was predicted, it will be easy for teachers, school authority or other related parties to determine the appropriate policies on the issue. Relatedly, this paper aimed to provide the prediction of students? performance in final examination by applying linear regression and multilayer perceptron in WEKA- in terms of accuracy, performance and error rate- to compare their feasibility. The basis of data was derived from extraction and analysis of e-learning logged-post in discussion forum and attendance. Based on the result, it has been concluded that multilayer perceptron provides better prediction results of final examination than linear regression.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123759408","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":"A navigation device utilizing body communication channel for mobile wearable systems","authors":"A. Bujnowski, Kamil Osiński, J. Wtorek","doi":"10.1109/HSI.2017.8004990","DOIUrl":"https://doi.org/10.1109/HSI.2017.8004990","url":null,"abstract":"A novel touch sensor utilizing a body communication technology is presented in the paper. The proposed device accepts orders (gestures) only from a person wearing it. Moreover, when comparing it to a similar, however an optical one, it appears as a less power consumable. Preliminary results of its properties examination are presented and discussed. Additionally, the developed sensor allows to measure a human body the electrical passive parameters thus, aside it performs a basic functionality it also delivers additional information on the user.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121086646","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}
Jin Hedian, Li Chunguagn, S. Li-ning, Huang Haiyan, Xu Jiacheng, Qu Wei
{"title":"To classify two-dimensional motion state of step length and walking speed by applying cerebral hemoglobin information","authors":"Jin Hedian, Li Chunguagn, S. Li-ning, Huang Haiyan, Xu Jiacheng, Qu Wei","doi":"10.1109/HSI.2017.8005032","DOIUrl":"https://doi.org/10.1109/HSI.2017.8005032","url":null,"abstract":"This paper presents a research on classifying walking speed and step length simultaneously by using cerebral hemoglobin information. Nine healthy subjects performed walking task spontaneously in three levels of speed and three levels of step length. Brain information of the subjects was measured by using functional near-infrared spectroscopy (fNIRS) technology. The differences between the oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb) were decomposed by wavelet packet. Feature vectors were extracted in both the time domain and frequency domain. Walking speed and step length was identified by applying support vector machine (SVM) method. The preliminary identification accuracy was 62.97%. This finding puts forward a new method for identifying two-dimensional state of lower limbs in level walking. And it lays a foundation for realizing autonomous control of walking-assistive equipment.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126902918","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":"Study on play specific to the saddle type interface for personal mobility","authors":"S. Yokota, D. Chugo, H. Hashimoto","doi":"10.1109/HSI.2017.8005046","DOIUrl":"https://doi.org/10.1109/HSI.2017.8005046","url":null,"abstract":"The saddle type human body movement interface uses not only translational movements but also a twisting movement for controlling a personal mobility. The saddle is mounted on a personal mobility through a universal joint having 3 axes, and follows human body movement. One axis following the body movement on forward/backward is used for making the control input (velocity) of a personal mobility. And two axes on translational right/left and twisting right/left are used for making the control input of angular velocity. For making these control inputs, appropriate plays on each axis should be considered, because play of an interface absorbs low precise and small human movement in order not to reflect these movement to a machine's movement for providing high usability. This paper, therefore, experimentally investigates typical ranges of play (software backlash) on the saddle type interface, and implements them into the control scheme for the personal mobility, and evaluate it.","PeriodicalId":355011,"journal":{"name":"2017 10th International Conference on Human System Interactions (HSI)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132828356","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}