{"title":"3D shape recovery of polyp using two light sources endoscope","authors":"Hiroyasu Usami, Y. Hanai, Y. Iwahori, K. Kasugai","doi":"10.1109/ICIS.2016.7550773","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550773","url":null,"abstract":"As a method to recover 3D shape under point light source and perspective projection, a method to recover the depth distribution has been proposed using optimization with both photometric and geometrical constraints which represents the relation between an interesting point and neighboring points under the assumption of Lambertian reflectance. This method assumes one light source at the same positions of viewing point and point light source although actual endoscope has two light sources. This paper proposes a new approach using a photometric constraint equation considering two light sources. The procedures are as follows. First, obtain depth distributions by optimizing photometric constraint under two light sources. Next, obtain the surface normal vector from depth using numerical difference at each point. Then the mapping between the obtained normal vector and true normal vector is learned by Radial Basis Function Neural Network (NN) for a Lambertian sphere and generalized to another target image. Finally, optimize the depth using photometric constraint to recover the final 3D shape. The validity of this method is confirmed in comparison with the previous methods via computer simulation and experiments using actual endoscope images.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130318609","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 formal approach for guiding architecture design with data constraints","authors":"Naoya Nitta","doi":"10.1109/ICIS.2016.7550874","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550874","url":null,"abstract":"The data managed in a software system is often controlled to behave dependently. Basically, dependent parts of the data can be controlled through their internal connections. However in a real-world system, dependencies among the data and its required behaviors are generally complex and designing its internal structure and control mechanism to satisfy all requirements becomes challenging. To cope with the problem, in this paper, we present a formal approach to guide an architecture design process so that given execution scenarios can be satisfied through iterative refinement of constraints among the data. For case studies, we applied our approach to a customer management system and a 3D game framework, and confirmed that a valid architectural design guide can be obtained.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"05 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130364636","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":"Image generation using generative adversarial networks and attention mechanism","authors":"Yuusuke Kataoka, Takashi Matsubara, K. Uehara","doi":"10.1109/ICIS.2016.7550880","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550880","url":null,"abstract":"For image generation, deep neural networks are trained to extract high-level features on natural images and to reconstruct the images from the features. However it is difficult to learn to generate images containing enormous contents. To overcome this difficulty, a network with an attention mechanism has been proposed. It is trained to attend to parts of the image and to generate images step by step. This enables the network to deal with the details of a part of the image and the rough structure of the entire image. The attention mechanism is implemented by recurrent neural networks. Additionally, the Generative Adversarial Networks (GANs) approach has been proposed to generate more realistic images. In this study, we present image generation where leverages effectiveness of attention mechanism and the GANs approach. We show our method enables the iterative construction of images and more realistic image generation than standard GANs and the attention mechanism of DRAW.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114613089","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}
Yuichiro Kataoka, Toru Nakashika, Ryo Aihara, T. Takiguchi, Y. Ariki
{"title":"Selection of an optimum random matrix using a genetic algorithm for acoustic feature extraction","authors":"Yuichiro Kataoka, Toru Nakashika, Ryo Aihara, T. Takiguchi, Y. Ariki","doi":"10.1109/ICIS.2016.7550890","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550890","url":null,"abstract":"This paper describes a selection technique of an optimum random matrix using a genetic algorithm for speech recognition based on random projections. Random projections have been suggested as a means of dimensionality reduction, where the original data are projected onto a subspace using a random matrix. Moreover, as we are able to produce various random matrices, it may be possible to find a transform matrix that is superior to conventional transformation matrices among random matrices. In this paper, a genetic algorithm is introduced to find an optimum random matrix. Its effectiveness is confirmed by word recognition experiments.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124691411","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":"Image retrieval system based on bag of view words model","authors":"Cheng Feng, Xiaohong Wang","doi":"10.1109/ICIS.2016.7550926","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550926","url":null,"abstract":"In this paper, the theory of bag of view words model is introduced for image retrieval, and a method to enhance accuracy rate of the model is provided. In addition, an image retrieval system is also constructed for movie posters. The system matches the pictures uploaded with the corresponding movie from the gallery, and is more accurate and efficient.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124797778","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":"Application of SVD technology in video recommendation system","authors":"Menghan Yan, Wenqian Shang, Zhenzhong Li","doi":"10.1109/ICIS.2016.7550930","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550930","url":null,"abstract":"The most direct access to evaluate what kinds of topics are valuable for video producers, and bring them inspiration is to seek subjects which specific groups concern currently. We can obtain massive user information from social networking platforms, large video sites and search engines, and then exploit the data to produce more practical works with the combination of business requirements. In views of the existing disadvantages of inferior scalability, sparsity problem and huge volume test data, the application of Singular Value Decomposition Method(SVD) actualize the unknown prediction score function of set of tests. The simulation results show that scalability, sparsity and omputational efficiency improved effectively.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"299 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124244462","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}
Abdul Mateen, Adia Khalid, Lal Khan, S. Majeed, Tooba Akhtar
{"title":"Vigorous algorithms to control urban vehicle traffic","authors":"Abdul Mateen, Adia Khalid, Lal Khan, S. Majeed, Tooba Akhtar","doi":"10.1109/ICIS.2016.7550740","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550740","url":null,"abstract":"Currently digital systems are mostly used in vehicle traffic, airplane and many other systems due to the exponential growth in the computational capabilities of processor based systems. This technology has minimized the effort, manpower and increased the traffic flow. Our research proposes algorithms for agent-based autonomous controller (ABAC) that will help to manage the road traffic in an efficient and secure way. These algorithms calculate the appropriate time for each side of the traffic signal as well as signal cycle time without human intervention. It also provides immediate and safe passage for an ambulance. The proposed algorithms use sound and sonic sensors that are used to identify the emergency vehicle with direction for immediate response and report to next signal for its smooth passage.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125380982","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":"Video annotation for players' tactics in sport competition","authors":"Na Jia, Chi Xu, Huiqun Zhao","doi":"10.1109/ICIS.2016.7550783","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550783","url":null,"abstract":"The video recorded tactics that a player applied in a sport competition are encoded to understandable semantics scripts for both human beings and computers. Such information is then embedded back into the sport video file. Thus, users can retrieve the contents of competition for purposes such as video analysis and tactics statistical analysis.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129306518","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 simple population based hybrid harmonic estimation algorithm","authors":"E. O. Tartan, H. Erdem","doi":"10.1109/ICIS.2016.7550767","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550767","url":null,"abstract":"This paper presents a new hybrid algorithm for harmonic estimation. The algorithm combines a simple fast population based search algorithm with Least Squares Method. It is based on the structural property of the harmonic estimation problem which implies that the signal model is linear in amplitude and nonlinear in phase. The hybrid algorithm uses the search algorithm for phase estimation and LS for amplitude estimation, iteratively. Exploiting the objective function defined according to the error of single harmonic's phase estimation, the proposed search algorithm distributes the population through equal intervals and simply narrows the search space sequentially in every generation. Unlike the other heuristic optimization algorithms that uses random distribution in initialization stage, the proposed method provides more robust convergence in the limits determined by the generation number. Simulation results show that the proposed hybrid algorithm not only gives accurate results but also significantly improves the computation time when compared with other heuristic optimization algorithms. Moreover this approach can be used to reduce the search duration when involved in other evolutionary optimization algorithms in a hybrid way and then can deal with frequency deviation and subharmonic estimation which are pitfalls for DFT based algorithms.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129773259","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":"Utilizing texts of picture book reviews for extracting children's behavioral characteristics in language acquisition","authors":"Hiroshi Uehara, Mizuho Baba, T. Utsuro","doi":"10.1109/ICIS.2016.7550851","DOIUrl":"https://doi.org/10.1109/ICIS.2016.7550851","url":null,"abstract":"Pointing behavior in childhood is typical developmental sign having strong correlation to his or her language development. This paper focuses on the pointing behavior accompanied by utterance during picture book reading. With this respect, we make use of picture books' review data amounting to approximately 320 thousand, and analyze the reviews reflecting the pointing behavior with children's utterance. The results show patterns of the pointing with utterance change corresponding to children's developmental stages. Also, one of the pointing patterns is found to have strong relationship with a certain type of picture books.","PeriodicalId":336322,"journal":{"name":"2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128046615","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}