{"title":"NOTES3D: Endoscopes learn to see 3-D - basic algorithms for a novel endoscope","authors":"J. Penne, K. Höller, Sophie Krüger, H. Feußner","doi":"10.5220/0002068401340139","DOIUrl":"https://doi.org/10.5220/0002068401340139","url":null,"abstract":"A process for the preparation of trimethylsilyl cyanide comprising reacting trimethylsilyl chloride with an approximately equimolar amount of an alkali metal cyanide in the presence of a catalytic amount of a heavy metal cyanide and in the presence of an aprotic solvent with a boiling point above about 150 DEG C., at a temperature between about 130 DEG and 250 DEG C. Advantageously the reaction temperature is between about 160 DEG and 220 DEG C., the alkali metal cyanide is sodium cyanide or potassium cyanide, the heavy metal cyanide is copper(I) cyanide, copper(II) cyanide, zinc cyanide or a complex compound of one of them with an alkali metal cyanide and is employed in about 1 to 8 mol % relative to the alkali metal cyanide, and the mixture of aprotic solvent, heavy metal cyanide and alkali metal chloride remaining in the reaction vessel when the reaction has ended is used directly as the reaction medium for a further batch.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131933473","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":"Traffic sign classification using error correcting techniques","authors":"Sergio Escalera, P. Radeva, O. Pujol","doi":"10.5220/0002058102810285","DOIUrl":"https://doi.org/10.5220/0002058102810285","url":null,"abstract":"Traffic sign classification is a challenging problem in Computer Vision due to the high variability of sign appearance in uncontrolled environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a classification technique for traffic signs recognition by means of Error Correcting Output Codes. Recently, new proposals of coding and decoding strategies for the Error Correcting Output Codes framework have been shown to be very effective in front of multiclass problems. We review the state-of-the-art ECOC strategies and combinations of problem-dependent coding designs and decoding techniques. We apply these approaches to the Mobile Mapping problem. We detect the sign regions by means of Adaboost. The Adaboost in an attentional cascade with the extended set of Haar-like features estimated on the integral shows great performance at the detection step. Then, a spatial normalization using the Hough transform and the fast radial symmetry is done. The model fitting improves the final classification performance by normalizing the sign content. Finally, we classify a wide set of traffic signs types, obtaining high success in adverse conditions.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124226316","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}
Tingting Jiang, Shengyong Chen, Q. Guan, Chunyan Yao
{"title":"Cylindrical b-spline model for representation and fitting of heart surfaces","authors":"Tingting Jiang, Shengyong Chen, Q. Guan, Chunyan Yao","doi":"10.5220/0002064800620068","DOIUrl":"https://doi.org/10.5220/0002064800620068","url":null,"abstract":"This disclosure relates to a novel class of 2-alkyl-3-haloisothiazolium salts. These salts have been found to be useful in controlling the growth of bacteria and fungi. They have also been found to be useful intermediates in the preparation of novel and known antibacterial and antifungal compounds.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121534228","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":"Automated tumor segmentation using level set methods","authors":"S. Lebonvallet, S. Khatchadourian, S. Ruan","doi":"10.5220/0002068301280133","DOIUrl":"https://doi.org/10.5220/0002068301280133","url":null,"abstract":"In the framework of detection, diagnostic and treatment planning of the tumours, the Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) have become the most efficient techniques for body and brain examination. Radiologists take usually several hours to segment manually the region of interest (ROI) on images to obtain some information about patient pathology. It is very time consuming. The aim of our study is to propose an automatic solution to this problem to help the radiologist’s work. This paper presents an approach of tumour segmentation based on a fast level set method. The results obtained by the proposed method dealing with both PET and MRI images are encouraging.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121368307","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. Nieto, Luis Unzueta, Andoni Cortés, Javier Barandiarán, O. Otaegui, Pedro J. Sánchez
{"title":"Real-time 3D Modeling of Vehicles in Low-cost Monocamera Systems","authors":"M. Nieto, Luis Unzueta, Andoni Cortés, Javier Barandiarán, O. Otaegui, Pedro J. Sánchez","doi":"10.5220/0003312104590464","DOIUrl":"https://doi.org/10.5220/0003312104590464","url":null,"abstract":"A new method for 3D vehicle modeling in low-cost monocamera surveillance systems is introduced in this paper. The proposed algorithm aims to resolve the projective ambiguity of 2D image observations by means of the integration of temporal information and model priors within a Markov Chain Monte Carlo (MCMC) method. The method is specially designed to work in challenging scenarios, with noisy and blurred 2D observations, where traditional edge-fitting or feature-based methods fail. Tests have shown excellent estimation results for traffic-flow video surveillance applications, that can be used to classify vehicles according to their length, width and height.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115345110","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":"Rectangular Empty Parking Space Detection using SIFT based Classification","authors":"H. Bhaskar, N. Werghi, S. Al-Mansoori","doi":"10.5220/0003358702140220","DOIUrl":"https://doi.org/10.5220/0003358702140220","url":null,"abstract":"In this paper, we describe a method of combining rectangle detection and scale invariant feature transform (SIFT) analysis for empty parking space detection. A parking space in a parking lot is represented as a rectangular region of pixels in an image captured from an aerial camera. Detecting rectangular parking spaces in a new image involves an alternating scheme of extracting peaks from the Radon transform for the whole image and filtering them against specific geometric and spatial constraints. We then compute SIFT descriptors from these detected rectangular parking spaces and further apply supervised classification methods for detecting empty parking spaces. We demonstrate the performance of our model on several synthetic and real data.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134613827","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}
Ignazio Infantino, C. Lodato, S. Lopes, Filippo Vella
{"title":"Implementation of an Intentional Vision System to Support Cognitive Architectures","authors":"Ignazio Infantino, C. Lodato, S. Lopes, Filippo Vella","doi":"10.5220/0002341100530062","DOIUrl":"https://doi.org/10.5220/0002341100530062","url":null,"abstract":"Manual mounting of large high density lead insertion connectors (1) onto circuit boards (3) is achieved by simultaneously engaging all connector leads (2) with a comb (9), sliding the engaged leads into alignment with receiving passageways (4) in the circuit board and pressing the connector leads into the receiving passageways. The comb has an exterior surface forming channels (10) corresponding in spatial relationship to the lead receiving passageways. A connector lead insertion apparatus (5, 6, 7, 8, 9, 10) is utilized in conjunction with the lead insertion method to hold the circuit board and connector in fixed position with respect to each other. The apparatus further permits the comb to be guided into proper position prior to engaging the connector leads.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121091722","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 new method for video soccer shot classification","authors":"Youness Tabii, M. O. Djibril, Y. Hadi, R. Thami","doi":"10.5220/0002051702210224","DOIUrl":"https://doi.org/10.5220/0002051702210224","url":null,"abstract":"A shot is often used as the basic unit for both video analysis and indexing. In this paper we present a new method for soccer shot classification on the basis of playfield segmentation. First, we detect the dominant color component, by supposing that playfield pixels are green (dominant color). Second, the segmentation process begins by dividing frames into a 3:5:3 format and then classifying them. The experimental results of our method are very promising, and improve the performance of shot detection.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121275903","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}
P. Agrafiotis, Elisavet (Ellie) Konstantina Stathopoulou, A. Georgopoulos, A. Doulamis
{"title":"HDR Imaging for Enchancing People Detection and Tracking in Indoor Environments","authors":"P. Agrafiotis, Elisavet (Ellie) Konstantina Stathopoulou, A. Georgopoulos, A. Doulamis","doi":"10.5220/0005456706230630","DOIUrl":"https://doi.org/10.5220/0005456706230630","url":null,"abstract":"Videos and image sequences of indoor environments with challenging illumination conditions often capture either brightly lit or dark scenes where every single exposure may contain overexposed and/or underexposed regions. High Dynamic Range (HDR) images contain information that standard dynamic range ones, often mentioned also as low dynamic range images (SDR/LDR) cannot capture. This paper investigates the contribution of HDR imaging in people detection and tracking systems. In order to evaluate this contribution of the HDR imaging in the accuracy and robustness of pedestrian detection and tracking in challenging indoor visual conditions, two state of the art trackers of different complexity were implemented. To this direction data were collected taking into account the requirements and real-life indoor scenarios and HDR frames were produced. The algorithms were applied to the SDR data and their corresponding HDR data and were compared and evaluated for their robustness and accuracy in terms of precision and recall. Results show that that the use of HDR images enhances the performance of the detection and tracking scheme, making it robust and more reliable.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115721797","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":"Automatic Video Zooming for Sport Team Video Broadcasting on Smart Phones","authors":"F. Lavigne, Fan Chen, X. Desurmont","doi":"10.5220/0002830101570163","DOIUrl":"https://doi.org/10.5220/0002830101570163","url":null,"abstract":"This paper presents a general framework to adapt the size of a sport team video extracted from TV to a small device screen. We use a soccer game context to describe the four main steps of our video processing framework: (1) A view type detector helps to decide whether the current frame of the video has to be resized or not. (2) If the camera point of view is far, a ball detector localizes the interesting area of the scene. (3) Then, the current frame is resized and centred on the ball, taking into account some parameters, such as the ball position and its speed. (4) At the end of the process, the score banner is detected and removed by an inpainting method.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116672259","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}