Deep probabilistic human pose estimation
The authors consider the problem of human pose estimation using probabilistic convolutional neural networks. They explore ways to improve human pose estimation accuracy on standard pose estimation benchmarks MPII human pose and Leeds Sports Pose (LSP) datasets using frameworks for probabilistic deep learning. Such frameworks transform deterministic neural network into a probabilistic one and allow sampling of independent and equiprobable hypotheses (different outputs) for a given input. Overlapping body parts and body joints hidden under clothes or other obstacles make the problem of human pose estimation ambiguous. In this context to get accurate estimation of joints’ position they use uncertainty in network's predictions, which is represented by variance of hypotheses, provided by a probabilistic convolutional neural network, and confidence is characterised by mean of them. Their work is based on current CNN cascades for pose estimation. They propose and evaluate three probabilistic convolutional neural networks built on top of deterministic ones with two probabilistic deep learning frameworks – DISCO networks and Bayesian SegNet. The authors evaluate their models on standard pose estimation benchmarks and show that proposed probabilistic models outperform base deterministic ones.
The article is devoted to the history and problems of creating interfaces. Shows the complexity and importance of effective interfaces, noted that this problem is a system of multilevel interdisciplinary. The new systems should be given serious attention to issues of human efficiency level. Man is still the leading element in determining the efficiency of any ergatic system. The main means of control in ergatic systems including computers, is the graphic manipulator (GM), with which to control the on-screen controls. Are the main styles of user interface. The most popular are GUI-interface (GUI - GraphicalUserInterface) and based on them WUI-interface (WUI-WebUserInterface). The development of equipment and technology of computer modeling led to the active introduction of virtual reality technology to ensure the inclusion of people in artificial worlds. Their main feature - full control of all the parameters of the development and the emergence of a sense of presence in people who live in these environments, which are called immersive. Technology induced environments allow a number of new, not generally applicable to the present, of interfaces using specially engineered virtual environments. Much attention is paid to creating the most advanced systems - systems contact management, which are the camera and sophisticated software. The drawbacks of modern non-contact control. Is being developed to create a contactless intelligent interface, which will allow: to control with data from a video camera, which is installed on your computer have a high noise immunity, clearly identify the user to recognize the situational environment, have an acceptable cost.
The volume contains the abstracts of the 12th International Conference "Intelligent Data Processing: Theory and Applications". The conference is organized by the Russian Academy of Sciences, the Federal Research Center "Informatics and Control" of the Russian Academy of Sciences and the Scientific and Coordination Center "Digital Methods of Data Mining". The conference has being held biennially since 1989. It is one of the most recognizable scientific forums on data mining, machine learning, pattern recognition, image analysis, signal processing, and discrete analysis. The Organizing Committee of IDP-2018 is grateful to Forecsys Co. and CFRS Co. for providing assistance in the conference preparation and execution. The conference is funded by RFBR, grant 18-07-20075. The conference website http://mmro.ru/en/.
In this paper, we take up the long-standing problem of how to recover 3-D shapes represented by a 2-D image, such as the image on the retina of the eye, or in a video camera. Our approach is biologically grounded in a theory of how the human visual system solves this problem, focusing on shapes that are mirror symmetrical in 3-D. A 3-D mirror-symmetrical shape can be recovered from a single 2-D orthographic or perspective image by applying several a priori constraints: 3-D mirror symmetry, 3-D compactness, and planarity of contours. From the computational point of view, the application of a 3-D symmetry constraint is challenging because it requires establishing 3-D symmetry correspondence among features of a 2-D image, which itself is asymmetrical for almost all viewing directions relative to the 3-D symmetrical shape. We describe new invariants of a 3-D to 2-D projection for the case of a pair of mirror-symmetrical planar contours, and we formally state and prove the necessary and sufficient conditions for detection of this type of symmetry in a single orthographic and perspective image.
We consider the problem of estimating 3-d structure from a single still image of an outdoor urban scene. Our goal is to efficiently create 3-d models which are visually pleasant. We chose an appropriate 3-d model structure and formulate the task of 3-d reconstruction as model fitting problem. Our 3-d models are composed of a number of vertical walls and a ground plane, where ground-vertical boundary is a continuous polyline. We achieve computational efficiency by special preprocessing together with stepwise search of 3-d model parameters dividing the problem into two smaller sub-problems on chain graphs. The use of Conditional Random Field models for both problems allows to various cues. We infer orientation of vertical walls of 3-d model vanishing points.
This work addresses the problem of video matting, that is extracting the opacity-layer of a foreground object from a video sequence. We introduce the notion of alpha-flow which corresponds to the flow in the opacity layer. The idea is derived from the process of rotoscoping, where a user-supplied object mask is smoothly interpolated between keyframes while preserving its correspondence with the underlying image. Our key contribution is an algorithm which infers both the opacity masks and the alpha-flow in an efficient and unified manner. We embed our algorithm in an interactive video matting system where the first and last frame of a sequence are given as keyframes, and additional user strokes may be provided in intermediate frames. We show high quality results on various challenging sequences, and give a detailed comparison to competing techniques.
Most of today’s machine learning techniques requires large manually labeled data. This problem can be solved by using synthetic images. Our main contribution is to evaluate methods of traffic sign recognition trained on synthetically generated data and show that results are comparable with results of classifiers trained on real dataset. To get a representative synthetic dataset we model different sign image variations such as intra-class variability, imprecise localization, blur, lighting, and viewpoint changes. We also present a new method for traffic sign segmentation, based on a nearest neighbor search in the large set of synthetically generated samples, which improves current traffic sign recognition algorithms.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.