Analyzing Structured Scenarios by Tracking People and Their Limbs

The analysis of human activities is a fundamental problem in computer vision. Though complex, interactions between people and their environment often exhibit a spatio-temporal structure that can be exploited during analysis. This structure can be leveraged to mitigate the effects of missing or noisy visual observations caused, for example, by sensor noise, inaccurate models, or occlusion. Trajectories of people and their hands and feet, often sufficient for recognition of human activities, lead to a natural qualitative spatio-temporal description of these interactions. This work introduces the following contributions to the task of human activity understanding: 1) a framework that efficiently detects and tracks multiple interacting people and their limbs, 2) an event recognition approach that integrates both logical and probabilistic reasoning in analyzing the spatio-temporal structure of multi-agent scenarios, and 3) an effective computational model of the visibility constraints imposed on humans as they navigate through their environment. The tracking framework mixes probabilistic models with deterministic constraints and uses AND/OR search and lazy evaluation to efficiently obtain the globally optimal solution in each frame. Our high-level reasoning framework efficiently and robustly interprets noisy visual observations to deduce the events comprising structured scenarios. This is accomplished by combining First-Order Logic, Allen's Interval Logic, and Markov Logic Networks with an event hypothesis generation process that reduces the size of the ground Markov network. When applied to outdoor one-on-one basketball videos, our framework tracks the players and, guided by the game rules, analyzes their interactions with each other and the ball, annotating the videos with the relevant basketball events that occurred. Finally, motivated by studies of spatial behavior, we use a set of features from visibility analysis to represent spatial context in the interpretation of human spatial activities. We demonstrate the effectiveness of our representation on trajectories generated by humans in a virtual environment

A Neural Network Model for Time-Series Forecasting

The paper presents some aspects regarding the use of pattern recognition techniques and neural networks for the activity evolution diagnostication and prediction by means of a set of indicators. Starting from the indicators set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indicators set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software for macroeconomic diagnostication and prediction during the years 2003-2010.time-series, pattern recognition, neural networks, multilayer perceptron, diagnostication, forecasting

Institutional critique. A philosophical investigation of its conditions and possibilities

'Institutional critique' is a term that refers to a range of diverse artistic practices and discourses that emerged at the end of the 1960s and that continue in the present. In spite of their differences, they all share a concern with the institutional conditioning of artists and artworks. Various historicizations of institutional critique (Alberro and Stimson, 2009; Raunig and Ray, 2009; Welchman, 2006) concur that one could distinguish two 'phases': artists of the 1960s and 1970s allegedly investigated the possibilities of an escape towards an 'outside' of the art institution, whereas those of the 1990s analysed the ways in which the artistic subject reproduced the structures of the art institution. Since the beginning of the 2000s various artists and authors have revisited the histories and legacies of institutional critique. This growing interest was triggered by the perceived intensification of a process that began at the end of the 1960s; it refers to the recuperation and neutralization of artistic types of critique by what Boltanski and Chiapello (2005) have called the 'new spirit' of capitalism. In this context, the Austrian philosopher Gerald Raunig and the members of the European Institute for Progressive Cultural Policies have proposed the hypothesis that 'a new phase' of institutional critique was to emerge. However, this proposition was based less on empirical evidence, than on a 'political and theoretical necessity to be found in the logic of institutional critique' (Raunig, 2009, 3). This thesis is a response to this set of circumstances. By asking 'what are the conditions and possibilities of institutional critique?' it investigates the categories of institutional critique's logic. My main argument is that a 'phase change' of institutional critique could and should be understood through the apparatus of Derridean deconstruction. This implies a criticism of the idea that one needs to escape the art institution in order to respond to urgencies stemming from the social, economic, and political realms (Truth Is Concrete Platform, 2012). At the same time, I will also refute the idea that institutional critique is trapped in the art institution (Fraser, 2009a). Institutional critique works on the remainder and rest that necessarily escapes the instituting will and intention of defining and describing in an exhaustive manner the whatness of what (art) is (Boltanski, 2011). I show that between critique and the art institution there is an irreducible relation of symbiosis and cohabitation, and that the deconstructive logic of institutional critique allows it to be both partner and adversary, at the same time, of the art institution

Mining Discriminative Triplets of Patches for Fine-Grained Classification

Fine-grained classification involves distinguishing between similar sub-categories based on subtle differences in highly localized regions; therefore, accurate localization of discriminative regions remains a major challenge. We describe a patch-based framework to address this problem. We introduce triplets of patches with geometric constraints to improve the accuracy of patch localization, and automatically mine discriminative geometrically-constrained triplets for classification. The resulting approach only requires object bounding boxes. Its effectiveness is demonstrated using four publicly available fine-grained datasets, on which it outperforms or achieves comparable performance to the state-of-the-art in classification

From Watts to Wall Street: a Situationist analysis of political violence

This chapter applies ‘The Decline and Fall of the Spectacle-Commodity Economy’ – the Situationist account of the Watts Rebellion (Los Angeles, 1965) – to the August riots (England, 2011) and the global Occupy movement that followed. It draws two conclusions: that both May ‘68 and Occupy were formed by the political violence that preceded them; and that, although the Situationist essay makes problematic claims about race, its assessment of the Spectacle-Commodity Economy remains valuable. In fact, if combined with intersectional theory, it can provide a useful counterbalance to identity politics that can prevent what Alain Badiou calls an ‘immediate riot’ from becoming a ‘historical riot’ by fragmenting mass social movements and undermining unity