International Conference on Computer Vision Theory and Applications最新文献

{"title":"Dynamic context driven human detection and tracking in meeting scenarios","authors":"Peng Dai, L. Tao, Guangyou Xu","doi":"10.5220/0002070200310038","DOIUrl":"https://doi.org/10.5220/0002070200310038","url":null,"abstract":"As a significant part of context-aware systems, human-centered visual processing is required to be adaptive and interactive within dynamic context in real-life situation. In this paper a novel bottom-up and top-down integrated approach is proposed to solve the problem of dynamic context driven visual processing in meeting scenarios. A set of visual detection, tracking and verification modules are effectively organized to extract rough-level visual information, based on which a bottom-up context analysis is performed through Bayesian Network. In reverse, results of scene analysis are applied as top-down guidance to control refined level visual processing. The system has been tested under real-life meeting environment that includes three typical scenarios: speech, discussion and meeting break. The experiments show the effectiveness and robustness of our approach within continuously changing meeting scenarios and dynamic context.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123630003","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":"Real-time Gender Recognition for Uncontrolled Environment of Real-life Images","authors":"Duan-Yu Chen, Kuan-Yi Lin","doi":"10.5220/0002823203570362","DOIUrl":"https://doi.org/10.5220/0002823203570362","url":null,"abstract":"Gender recognition is a challenging task in real life images and surveillance videos due to their relatively low-resolution, under uncontrolled environment and variant viewing angles of human subject. Therefore, in this paper, a system of real-time gender recognition for real life images is proposed. The contribution of this work is fourfold. A skin-color filter is first developed to filter out non-face noises. In order to make the system robust, a mechanism of decision making based on the combination of surrounding face detection, context-regions enhancement and confidence-based weighting assignment is designed. Experimental results obtained by using extensive dataset show that our system is effective and efficient in recognizing genders for uncontrolled environment of real life images.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123285017","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":"Recurrence Matrices for Human Action Recognition","authors":"V. Traver, P. Agustí, F. Pla","doi":"10.5220/0004216202710276","DOIUrl":"https://doi.org/10.5220/0004216202710276","url":null,"abstract":"One important issue for action characterization consists of properly capturing temporally related information. In this work, recurrence matrices are explored as a way to represent action sequences. A recurrence matrix (RM) encodes all pair-wise comparisons of the frame-level descriptors. By its nature, a recurrence matrix can be regarded as a temporally holistic action representation, but it can hardly be used directly and some descriptor is therefore required to compactly summarize its contents. Two simple RM-level descriptors computed from a given recurrence matrix are proposed. A general procedure to combine a set of RM-level descriptors is presented. This procedure relies on a combination of early and late fusion strategies. Recognition performances indicate the proposed descriptors are competitive provided that enough training examples are available. One important finding is the significant impact on performance of both, which feature subsets are selected, and how they are combined, an issue which is generally overlooked.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121678938","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":"Robust Face Alignment Using Convolutional Neural Networks","authors":"S. Duffner, Christophe Garcia","doi":"10.5220/0001073200300037","DOIUrl":"https://doi.org/10.5220/0001073200300037","url":null,"abstract":"Face recognition in real-world images mostly relies on three successive steps: face detection, alignment and identification. The second step of face alignment is crucial as the bounding boxes produced by robust face detection algorithms are still too imprecise for most face recognition techniques, i.e. they show slight variations in position, orientation and scale. We present a novel technique based on a specific neural architecture which, without localizing any facial feature points, precisely aligns face images extracted from bounding boxes coming from a face detector. The neural network processes face images cropped using misaligned bounding boxes and is trained to simultaneously produce several geometric parameters characterizing the global misalignment. After having been trained, the neural network is able to robustly and precisely correct translations of up to ±13% of the bounding box width, in-plane rotations of up to ±30◦ and variations in scale from 90% to 110%. Experimental results show that 94% of the face images of the BioID database and 80% of the images of a complex test set extracted from the internet are aligned with an error of less than 10% of the face bounding","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123916501","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":"Lightweight Computer Vision Methods for Traffic Flow Monitoring on Low Power Embedded Sensors","authors":"M. Magrini, D. Moroni, G. Pieri, O. Salvetti","doi":"10.5220/0005361006630670","DOIUrl":"https://doi.org/10.5220/0005361006630670","url":null,"abstract":"Nowadays pervasive monitoring of traffic flows in urban environment is a topic of great relevance, since the information it is possible to gather may be exploited for a more efficient and sustainable mobility. In this paper, we address the use of smart cameras for assessing the level of service of roads and early detect possible congestion. In particular, we devise a lightweight method that is suitable for use on low power and low cost sensors, resulting in a scalable and sustainable approach to flow monitoring over large areas. We also present the current prototype of an ad hoc device we designed and report experimental results obtained during a field test.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"39 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113956987","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 scheme for contour detection","authors":"Gopal Datt Joshi, J. Sivaswamy","doi":"10.5220/0001374702360242","DOIUrl":"https://doi.org/10.5220/0001374702360242","url":null,"abstract":"We present a computationally simple and general purpose scheme for the detection of all salient object contours in real images. The scheme is inspired by the mechanism of surround influence that is exhibited in 80% of neurons in the primary visual cortex of primates. It is based on the observation that the local context of a contour significantly affects the global saliency of the contour. The proposed scheme consists of two steps: first find the edge response at all points in an image using gradient computation and in the second step modulate the edge response at a point by the response in its surround. In this paper, we present the results of implementing this scheme using a Sobel edge operator followed by a mask operation for the surround influence. The proposed scheme has been tested successfully on a large set of images. The performance of the proposed detector compares favourably both computationally and qualitatively, in comparison with another contour detector which is also based on surround influence. Hence, the proposed scheme can serve as a low cost preprocessing step for high level tasks such shape based recognition and image retrieval.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134240657","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":"Novel 3D Game-like Applications Driven by Body Interactions for Learning Specific Forms of Intangible Cultural Heritage","authors":"E. Yilmaz, D. Ugurca, C. Sahin, F. Dagnino, M. Ott, F. Pozzi, K. Dimitropoulos, F. Tsalakanidou, A. Kitsikidis, S. A. Kork, Kele Xu, B. Denby, P. Roussel-Ragot, P. Chawah, L. Crevier-Buchman, M. Adda-Decker, S. Dupont, B. Picart, J. Tilmanne, M. Alivizatou, L. Hadjileontiadis, V. Charisis, A. Glushkova, C. Volioti, A. Manitsaris, E. Hemery, F. Moutarde, N. Grammalidis","doi":"10.5220/0005456606510660","DOIUrl":"https://doi.org/10.5220/0005456606510660","url":null,"abstract":"The main objective of the EU FP7 ICT i-Treasures project is to build a public and expandable platform to enable learning and transmission of rare know-how of intangible cultural heritage. A core part of this platform consists of game-like applications able to support teaching and learning processes in the ICH field. We have designed and developed four game-like applications (for Human Beat Box singing, Tsamiko dancing, pottery making and contemporary music composition), each corresponding to one of the ICH use cases of i-Treasures project. A first preliminary version of these applications is currently available for further validation, evaluation and demonstration within the project. We have encountered a number of issues, most of which derive from the peculiarities of the ICH domains addressed by the project, and many have already been resolved/ The evaluation results are expected to lead to further optimization of these","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133256382","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":"Deformable structures localization and reconstruction in 3D images","authors":"D. Moroni, S. Colantonio, O. Salvetti, M. Salvetti","doi":"10.5220/0002071202150222","DOIUrl":"https://doi.org/10.5220/0002071202150222","url":null,"abstract":"This invention is directed to a method for treating the surface of photothermally crystallizable chemically-machinable glass-ceramic articles to render them non-sticking when brought into contact with certain organic materials. More particularly, the invention is drawn to the treatment of photothermally crystallizable, chemically-machinable glass-ceramic head pads for use in conjunction with information storage discs with SO2 vapors to render them non-sticking with respect to those discs.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131435249","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":"On board camera perception and tracking of vehicles","authors":"J. M. Collado, C. Hilario, J. M. Armingol, A. D. L. Escalera","doi":"10.5220/0002066600570066","DOIUrl":"https://doi.org/10.5220/0002066600570066","url":null,"abstract":"In this paper a visual perception system for Intelligent Vehicles is presented. The goal of the system is to perceive the surroundings of the vehicle looking for other vehicles. Depending on when and where they have to be detected (overtaking, at long range) the system analyses movement or uses a vehicle geometrical model to perceive them. Later, the vehicles are tracked. The algorithm takes into account the information of the road lanes in order to apply some geometric restrictions. Additionally, a multi-resolution approach is used to speed up the algorithm allowing real-time working. Examples of real images show the validation of the algorithm. 1 Perception in Intelligent Vehicles Human errors are the cause of most of traffic accidents, therefore can be reduced but not completely eliminated with educational campaigns. That is why the introduction of environment analysis by sensors is being researched. These perception systems receive the name of Advanced Driver Assistance Systems (ADAS) and it is expected that will be able to reduce the number, danger and severity of traffic accidents. Several ADAS, which nowadays are being researched for Intelligent Vehicles, are based on Computer Vision, among others Adaptive Cruise Control (ACC), which has to detect and track other vehicles. Now, commercial equipments are based on distance sensors like radars or LIDARs. Both types of sensors have the advantages of providing a direct distance measurement of the obstacles in front of the vehicle, are easily integrated with the vehicle control, are able to work under bad weather conditions, and lighting conditions do not affect them very much. The economical cost for LIDARs and a narrow field of view of radars are inconveniences that make Computer Vision (CV) an alternative or complementary sensor. Although it is not able to work under bad weather conditions and its information is much difficult to process, it gives a richer description of the environment that surrounds the vehicle. From the point of view of CV, the research on vehicle detection based on an onboard system can be classified in three main groups. Bottom-up or feature-based, where the algorithms looked sequentially for some features that define a vehicle. But they have two drawbacks: the vehicle is lost if one feature is not enough present in the image and false tracks can deceive the algorithm. Top-down or model-based, where there are one or several models of vehicles and the best model is found in the image through a likelihood function. They are more robust than the previous algorithms, but slower. The algorithm presented in this paper follows this approach. The third approach is learning-based. Mainly, they are based on Neural Networks (NN). Many images are needed to train the network. They are usually used together with a bottom-up algorithm to check if a vehicle has been actually detected. Otherwise, they have to scan the whole image and they are very slow. A previous detection of the road l","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"15 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132089533","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":"Variational Bayes with Gauss-Markov-Potts Prior Models for Joint Image Restoration and Segmentation","authors":"H. Ayasso, A. Mohammad-Djafari","doi":"10.5220/0001091805710576","DOIUrl":"https://doi.org/10.5220/0001091805710576","url":null,"abstract":"In this paper, we propose a family of non-homogeneous Gauss-Markov fields with Potts region labels model for images to be used in a Bayesian estimation framework, in order to jointly restore and segment images degraded by a known point spread function and additive noise. The joint posterior law of all the unknowns ( the unknown image, its segmentation hidden variable and all the hyperparameters) is approximated by a separable probability laws via the variational Bayes technique. This approximation gives the possibility to obtain practically implemented joint restoration and segmentation algorithm. We will present some preliminary results and comparison with a MCMC Gibbs sampling based algorithm","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"35 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123290073","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}