296,737 research outputs found

    Cinematic and aesthetic cartographies of subjective mutation

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    This article exmaines the use of cinema as a mapping of subjective mutation in the work of Deleuze, Gauttari and Berardi. Drawing on Deleuze's distinciton between the reduction of the art-work to the symptom and the idea of art as symptomatology, the article focuses on Berardi's use of cinematic examples, posing the quesiton in each case of to what extent they function as symptomatologies or mere symptoms of cultural and subjective mutations in examples ranging from Bergman's Persona to Van Sant's Elephant to finish on speculations about Fincher's The Social Network as a cirtical engagement with subjective mutation in the 21st Century

    Mapping the unseen: making sense of the subjective image.

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    It used to be thought that photography, as a kind of automatic mapping, could provide an objective view of the world. Now we are aware of the power of framing and other interventions between what is 'out there' and what is captured in depiction. Perhaps even perception, let alone depiction, shares this subjectivity? The Sapir-Whorf hypothesis holds that different cultures actually see the world in different ways, as evidenced and influenced by concepts in their languages – though this idea has been derided, for example by Pinker. A key difficulty is that the word subjectivity is bandied about without care for its different meanings and without distinguishing the many forms it takes in the graphic image. If into this muddle we introduce the idea of interactivity, still greater confusion easily follows. The chapter brings some order to different kinds and levels of subjectivity by documenting how they are reflected in forms of graphical mapping. In the process, it becomes clear how significant is the change in media technologies from those bound by the conventional rectangles of the page and screen to media which are interactive, pervasive, multimodal, physical and social

    Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

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    High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques

    Subjective Mapping

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    There are a variety of domains where it is desirable to learn a representation of an environment defined by a stream of sensori-motor experience. This dissertation introduces and formalizes subjective mapping, a novel approach to this problem. A learned representation is subjective if it is constructed almost entirely from the experience stream, minimizing the requirement of additional domain-specific information (which is often not readily obtainable). In many cases the observational data may be too plentiful to be feasibly stored. In these cases, a primary feature of a learned representation is that it be compact---summarizing information in a way that alleviates storage demands. Consequently, the first key insight of the subjective mapping approach is to phrase the problem as a variation of the well-studied problem of dimensionality reduction. The second insight is that knowing the effects of actions is critical to the usefulness of a representation. Therefore enforcing that actions have a consistent and succinct form in the learned representation is also a key requirement. This dissertation presents a new framework, action respecting embedding (ARE), which builds on a recent effective dimensionality reduction algorithm called maximum variance unfolding, in order to solve the newly introduced subjective mapping problem. The resulting learned representations are shown to be useful for reasoning, planning and localization tasks. At the heart of the new algorithm lies a semidefinite program leading to questions about ARE's ability to handle sufficiently large input sizes. The final contribution of this dissertation is to provide a divide-and-conquer algorithm as a first step to addressing this issue

    Is There Evidence of Pessimism and Doubt in Subjective Distributions? A Comment on Abel

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    Abel (2002) shows that pessimism and doubt in the subjective distribution of the growth rate of consumption reduce the riskfree rate puzzle and the equity premium puzzle. We quantify the amount of pessimism and doubt in survey data on US consumption and income. Individual forecasters are in fact pessimistic, but show marked overconfidence rather than doubt. Whether this implies that overconfidence should be built into Abel's model depends on how the empirically heterogeneous subjective distributions are mapped into the distribution of a fictitious representative agent. We work out the form of this mapping in an Arrow-Debreu economy and show that the equity premium increases with the dispersion of beliefs. We then estimate this aggregate distribution and find little evidence of either overconfidence or doubt.Equity premium; Riskfree rate; Aggregation of beliefs; Survey of Professional Forecasters; Livingston Survey
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