Human focused action localization in video

We propose a novel human-centric approach to detect and localize human actions in challenging video data, such as Hollywood movies. Our goal is to localize actions in time through the video and spatially in each frame. We achieve this by first obtaining generic spatio-temporal human tracks and then detecting specific actions within these using a sliding window classifier. We make the following contributions: (i) We show that splitting the action localization task into spatial and temporal search leads to an efficient localization algorithm where generic human tracks can be reused to recognize multiple human actions; (ii) We develop a human detector and tracker which is able to cope with a wide range of postures, articulations, motions and camera viewpoints. The tracker includes detection interpolation and a principled classification stage to suppress false positive tracks; (iii) We propose a track-aligned 3D-HOG action representation, investigate its parameters, and show that action localization benefits from using tracks; and (iv) We introduce a new action localization dataset based on Hollywood movies. Results are presented on a number of real-world movies with crowded, dynamic environment, partial occlusion and cluttered background. On the Coffee&Cigarettes dataset we significantly improve over the state of the art. Furthermore, we obtain excellent results on the new Hollywood–Localization dataset

Why do we need a lump of money? Reflections on Crisis and Struggles around Reproductive Labour.

Artykuł rozważa kwestię dochodu podstawowego z perspektywy feministycznej ekologii politycznej, wykorzystującej kategorię pracy reprodukcyjnej ludzi i przyrody. W pierwszej części nawiązujemy do Kampanii na rzecz Płacy za pracę domową – prekursorki dochodu podstawowego, która kwestię dochodów wpisywała w problematykę relacji między patriarchatem a kapitalizmem, co nadawało Kampanii rewolucyjny wymiar. W dalszej części artykuł przywołuje trzy aktualne walki społeczne, które są podstawą do dalszych rozważań na temat zasadności rozwiązania takiego jak dochód podstawowy. Z jednej strony naświetla sytuację kryzysu opieki w Polsce, narastającego wraz z neoliberalnymi reformami ostatnich 25 lat. Z drugiej rozwija problematykę kryzysu ekologicznego, którego rozwiązanie trzeba uwzględnić w każdej teorii i strategii antykapitalistycznej. Niniejszy artykuł jest próbą odpowiedzi na pytanie, czy postulat płacy za pracę reprodukcyjną/produkcyjną ma dalej sens w dobie neoliberalnego kapitalizmu.The paper discusses basic income in the context of feminist political ecology using the concepts of reproductive labor, both performed by people and by nature. In the first part we elaborate on Wages for Housework campaign as a forerunner of the idea of basic income. The campaign inscribed the concept of income into intersectional relation between patriarchy and capitalism what was a key element of its revolutionary dimension. In the second part we analyze three different social struggles in order to create a ground for further reflections over the legitimacy such tools (and resolutions) as basic income. On the one hand the paper highlights some elements of the crisis of social reproduction, brought and further deepen by neoliberal reforms in Poland over the 25 years. On the other hand, it speaks to the issues of ecological crisis which needs to be taken into account in every anti-capitalist theory or strategy. Thus, the article aims to investigate if the wage demands for both reproductive and productive labor are still relevant in the era of neoliberal capitalism

Constructing Category Hierarchies for Visual Recognition

International audienceClass hierarchies are commonly used to reduce the complexity of the classification problem. This is crucial in situations when one has to deal with multiple categories. In this work, we evaluate the suitability of class hierarchies currently constructed for visual recognition. We show that top-down as well as bottom-up approaches that are commonly used to automatically construct hierarchies, incorporate assumptions about separability of classes that cannot be fulfilled in the case of visual recognition of a large number of object categories. We propose a modification which is appropriate for most top-down approaches. It allows to construct better class hierarchies that postpone decisions in the presence of uncertainty and thus provide higher recognition accuracy. We also compare our method to flat one-against-all approach and show how to control the speed-for-accuracy trade-off by using our method. For the experimental evaluation, we use the Caltech-256 visual object classes dataset and compare to the state-of-the-art

Accurate Object Localization with Shape Masks

International audienceThis paper proposes an object class localization approach which goes beyond bounding boxes, as it also determines the outline of the object. Unlike most current localization methods, our approach does not require any hypothesis parameter space to be defined. Instead, it directly generates, evaluates and clusters shape masks. Thus, the presented framework produces much richer answers to the object class localization problem. For example, it easily learns and detects possible object viewpoints and articulations, which are often well characterized by the object outline. We evaluate the proposed approach on the challenging natural-scene Graz-02 object classes dataset. The results demonstrate the extended localization capabilities of our method

Localisation of exogenous surfactants in cell membranes in the air-blood barrier : rat model

The use of exogenous surfactants has been introduced into the therapy of patients of different ages. Much better results have been obtained in the treatment of respiratory distress syndrome with surfactants enriched with surfactant proteins. In the following study we used protein-containing surfactants (survanta and curosurf). The aim of the following study was to determine the localisation of artificial surfactants in the lung tissue. Using the Immunogold Technique, biotinylated surfactant proteins were traced in the air-blood barriers. In all lungs the exogenous surfactant was present only in some alveoli. In these parts small areas of atelectasis as well as oedema and transudate accumulation were seen. These changes were less severe after biotinylated curosurf treatment. In electron microscope studies we found surfactant elements in the air-blood barrier and other structures of the alveolar septa. Immunogold studies confirm the presence of biotynylated surfactant in the elements of the air-blood barrier

Report from the research: "The factory of culture – paid and voluntary work at cultural festivals"

The research material is based on in-depth, partially structured interviews. However, the scope of topics was very wide and conversations mostly referred to: problems that the employees encountered at work, their motivation, expectations towards current work, as well as their future prospects. Answers that gradually appeared in the interviews have been then confronted with the analysis of data and documents that the Ministry of Culture and National Heritage made available. Budgets of particular festivals and general data on their financial support have also been confronted with the interviews. Such an analysis gave us a stronger, structural base for conclusions made over the interpretation of interviews. One question that surprised us, but also showed us the benefits of the grounded theory, was the fact that data obtained from interviews mirrored the data from the documents. In total there were 48 interviews with the employees, co-workers and volunteers who worked at 12 festivals financed by the Ministry of Culture and National Heritage located in 6 different cities in Poland

Localisation of exogenous surfactants in cell membranes in the air-blood barrier: rat model

The use of exogenous surfactants has been introduced into the therapy of patients of different ages. Much better results have been obtained in the treatment of respiratory distress syndrome with surfactants enriched with surfactant proteins. In the following study we used protein-containing surfactants (survanta and curosurf). The aim of the following study was to determine the localisation of artificial surfactants in the lung tissue. Using the Immunogold Technique, biotinylated surfactant proteins were traced in the air-blood barriers. In all lungs the exogenous surfactant was present only in some alveoli. In these parts small areas of atelectasis as well as oedema and transudate accumulation were seen. These changes were less severe after biotinylated curosurf treatment. In electron microscope studies we found surfactant elements in the air-blood barrier and other structures of the alveolar septa. Immunogold studies confirm the presence of biotynylated surfactant in the elements of the air-blood barrier

Simplified firefly algorithm for 2D image key-points search

In order to identify an object, human eyes firstly search the field of view for points or areas which have particular properties. These properties are used to recognise an image or an object. Then this process could be taken as a model to develop computer algorithms for images identification. This paper proposes the idea of applying the simplified firefly algorithm to search for key-areas in 2D images. For a set of input test images the proposed version of firefly algorithm has been examined. Research results are presented and discussed to show the efficiency of this evolutionary computation method.Comment: Published version on: 2014 IEEE Symposium on Computational Intelligence for Human-like Intelligenc

Will person detection help bag-of-features action recognition?

Bag-of-feature (BoF) models currently achieve state-of-the-art performance for action recognition. While such models do not explicitly account for people in video, person localization combined with BoF is expected to give further improvement for action recognition. The purpose of this paper is to validate this assumption and to quantify the improvements in action recognition expected from current and future person detectors. Given locations of people in video, we find that---somewhat surprisingly---background suppression leads only to a limited gain in performance. This holds for actions in both simple and complex scenes. On the other hand, we show how spatial locations of people enable to incorporate strong geometrical constraints in BoF models and in this way to improve the accuracy of action recognition in some cases. Our conclusions are validated with extensive experiments on three datasets with varying complexity, basic KTH, realistic UCF Sports and challenging Hollywood

Local Features and Kernels for Classification of Texture and Object Categories: An In-Depth Study

Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations and learns a Support Vector Machine classifier with kernels based on two effective measures for comparing distributions, the Earth Mover's Distance and the chi-square distance. We first evaluate the performance of our approach with different keypoint detectors and descriptors, as well as different kernels and classifiers. We then conduct a comparative evaluation with several state-of-the-art recognition methods on four texture and five object databases. On most of these databases, our implementation exceeds the best reported results and achieves comparable performance on the rest. Finally, we investigate the influence of background correlations on recognition performance via extensive tests on the PASCAL database, for which ground-truth object localization information is available. Our experiments demonstrate that image representations based on distributions of local features are surprisingly effective for classification of texture and object images under challenging real-world conditions, including significant intra-class variations and substantial background clutter.Les méthodes basées sur des descripteurs d'images locaux ont récemment donné de bons résultats en reconnaissance d'objets et de textures. Cet article évalue la pertinence d'une représentation d'image par une distribution (signature, histogramme) de descripteurs calculés en des points d'intérêt, et d'une classification par Machine à Vecteur Support dont les noyaux utilisent des mesures adaptées à la comparaison de distributions (Earth Mover Distance, chi-square). Dans un premier temps nous évaluons la performance de notre approche avec différentes combinaisons de détecteurs de points d'intérêt, de descripteurs, de noyaux et de classifieurs. Puis nous comparons nos résultats avec des méthodes de l'état de l'art sur quatre bases de textures et cinq bases d'objets. Sur la plupart de ces bases, nos performances sont meilleures que celles de l'état de l'art et comparables pour le reste. Enfin, nous mesurons l'influence de la corrélation des fonds sur les performances de reconnaissance sur la base PASCAL, pour laquelle on dispose de la localisation exacte des objets. Nos expérimentations démontrent que la représentation d'images à base de distribution de descripteurs locaux est très efficace pour la classification d'objets et de textures, dans des conditions réelles telles que de fortes variations intra-classes et un fond complexe