The Epicurean Parasite: Horace, Satires 1.1-3

We have learned a great deal in recent years about reading Horace\u27s satires; there is now widespread agreement that the speaker of the satires is himself a character within them, a persona. Such a persona may be most effective when it has obvious connections with its creator, but that fact does not preclude the exaggeration of reality, or even its complete inversion. For Horace the implications of this approach are exciting: instead of a poet discoursing with cheerful earnestness on morality, on poetry and on his daily life, we have a fictional character, whom we do not have to take seriously at all.The three diatribe satires present us with a character so absurd that they have been taken, I think rightly, as parodies. Although the poems were once appreciated as effective moralising sermons, even their admirers found it hard to justify the lack of intellectual coherence, to say nothing of the astonishing vulgarity of the second satire. As parodies, however, the poems are wonderfully successful. The speaker trots out a series of banalities: ‘people should be content with who they are’; ‘people should not go to extremes’; ‘people should be consistent’. But he invariably gets distracted, goes off on tangential rants, and makes a fool of himself. The moralist of the first three satires is, to put it bluntly, a jerk

Long range facial image acquisition and quality

Abstract This chapter introduces issues in long range facial image acquisition and measures for image quality and their usage. Section 1, on image acquisition for face recognition discusses issues in lighting, sensor, lens, blur issues, which impact short-range biometrics, but are more pronounced in long-range biometrics. Section 2 introduces the design of controlled experiments for long range face, and why they are needed. Section 3 introduces some of the weather and atmospheric effects that occur for long-range imaging, with numerous of examples. Section 4 addresses measurements of “system quality”, including image-quality measures and their use in prediction of face recognition algorithm. That section introduces the concept of failure prediction and techniques for analyzing different “quality ” measures. The section ends with a discussion of post-recognition ”failure prediction ” and its potential role as a feedback mechanism in acquisition. Each section includes a collection of open-ended questions to challenge the reader to think about the concepts more deeply. For some of the questions we answer them after they are introduced; others are left as an exercise for the reader. 1 Image Acquisition Before any recognition can even be attempted, they system must acquire an image of the subject with sufficient quality and resolution to detect and recognize the face. The issues examined in this section are the sensor-issues in lighting, image/sensor resolution issues, the field-of view, the depth of field, and effects of motion blur