Stanley Cavell’s account of aesthetic judgment has two components. The first is a feeling: the judge has to see, hear, ‘dig’ something in the object being judged, there has to be an ‘emotion’ that the judge feels and expresses. The second is the ‘discipline of accounting for [the judgment]’, a readiness to argue for one’s aesthetic judgment in the face of disagreement. The discipline of accounting for one’s aesthetic judgments involves what Nick Riggle has called a norm of convergence: the (...) judge aims to get one’s audience to taste see or hear what the judge tastes or sees or hears in the object being judged. Because of the unmistakable difficulty in reaching agreement in aesthetic judgment, Riggle has denied that aesthetic judgment requires a convergence norm and has proposed instead that it requires ‘a kind of harmony of individuality’ (which Riggle calls ‘vibing’). We argue that Cavell offers a version of the convergence norm that is distinct from those that Riggle criticizes, namely Kant’s demand for agreement and Andy Egan’s presupposition of similarity in dispositions in ‘non-defective’ aesthetic conversations. Cavell’s version of the convergence norm is ‘the hope of agreement’. One can hope that one’s audience will agree with one’s aesthetic judgments even when one isn’t in a position to demand agreement or to presuppose similarity in the dispositions that would make agreement more likely. Cavell’s distinct convergence norm avoids Riggle’s criticisms and contributes to a richer account of what’s going on when we disagree about aesthetic matters. (shrink)

Philosophers often write in a particular mood; their work is playful, strident, strenuous, or nostalgic. On the face of it, these moods contribute little to a philosophical argument and are merely incidental. However, I will argue that the cognitive science of moods and emotions offers us reasons to suspect that mood is relevant for philosophical texts. I use examples from Friedrich Nietzsche and Rudolph Carnap to illustrate the role moods play in their arguments. As readers and writers of philosophical texts, (...) we do well to attend to mood. (shrink)

This essay investigates a particular form of “affection” that has been neglected by the phenomenological tradition. This particular phenomenon is often referred to as the vibe, vibrations, or some variation thereof. This essay rearticulates “the vibe” as bodily emanation: human beings emanate feeling that is experienced by and through our bodies. My study of bodily emanation begins with Edmund Husserl’s notion of affectivity and then moves to Eugene T. Gendlin’s notion of the sentient body. This discussion enables my (...) own argument: Our bodies do not simply respond to the world in a sentient fashion, but also solicit sentience from one another. This solicitation of sentience is the basis of bodily emanation. I explicate bodily emanation through two realms of experience: the pre-conscious and the conscious. The first realm designates the manner in which our bodies summon emanation from one another in a continuous, multilateral fashion. Such preconscious solicitation precedes our conscious control and recognition. The second realm designates our ability to willfully project and direct particular vibes for particular purposes. This latter realm is what most people think of when they refer to “the vibe.” In general, this essay provides a detailed account of a particular phenomenon that most of us experience, but do not fully consider or attend to. (shrink)

An exploration of the production, transmission, and mutation of affective tonality—when sound helps produce a bad vibe.

Why are cities looking more and more alike? Why do hipster coffee shops and clothing boutiques all share that same vibe? One answer is that gentrification represents an invasive force that forcibly re-models cities, from the top-down, to meet the monotone eye of the gentrifier. Gentrification brings in external developers and designers, who create new businesses which all meet that one monotonous aesthetic mold. But I suggest, using work from Quill Kukla and Jane Jacobs, that this top-down model of (...) gentrification is incomplete. Gentrification also incentivizes local residents to remake their own businesses and properties to meet that monotone eye. Gentrification is a pressure which pushes cities to meet a universalized and therefore homogenized taste, rather than letting diverse tastes flourish. (This piece originally published as part of a symposium on Quill Kukla's City Living.). (shrink)

Studios resist reductive analyses. Although isolated, they have their own frontstages and backstages, and like the laboratories studied by Knorr-Cetina, function as more than simply “internal environments.” The placeness of studios leaves both audible traces (the early reflections of sounds) and visible ones, if we think of those studios that become shrines or pilgrimage sites, or photo or video documentation of studios that provide the outside world a brief glimpse into the interior isolation of recording studio life. It would seem (...) that major facilities such as Abbey Road, Ocean Way or Sun Records are emphatically not “placeless place[s]” (Gieryn 2008), nor are they decontextualized from their immediate geographic surroundings. -/- Although atomized project studios (including bedroom studios, garages, and barns) may not immediately appear to be embedded within the social relations of a bounded local culture, many such studios are embedded within the social relations of specific online networked cultures,20 as is evinced by the vibrant online recording engineer communities that support everything from amateur acoustician pedagogy to advanced mixing techniques and even online mixing/remixing competitions. Such studios can be considered as “local anchoring points in the cultural metropolises of the global urban network” (Watson, Hoyler and Mager 2009). Knorr-Cetina (1992) suggests something similar when she discusses how laboratories function not just as “internal environments” but rather as “a link between internal and external environments, a border in a wider traffic of objects and observations”. Like their larger counterparts, project studios are acoustic environments isolated from various perceived outsides, use the very same technologies of audition to make up for the constrained paths of audibility, and similarly shape the kinds of musical and social practices that can transpire within (even if this shaping process effectively restricts the studio’s usage to a single musician at a time). I argue that the more we wish to understand the vibe and sound of the studios, the more we may wish to consider the studio as an active agent in the process of recording production, an actor in the social worlds that inhabit its very wombs and bunkers. (shrink)

In the research of motion video, the existing target detection methods are susceptible to changes in the motion video scene and cannot accurately detect the motion state of the target. Moving target detection technology is an important branch of computer vision technology. Its function is to implement real-time monitoring, real-time video capture, and detection of objects in the target area and store information that users are interested in as an important basis for exercise. This article focuses on how to efficiently (...) perform motion detection on real-time video. By introducing the mathematical model of image processing, the traditional motion detection algorithm is improved and the improved motion detection algorithm is implemented in the system. This article combines the advantages of the widely used frame difference method, target detection algorithm, and background difference method and introduces the moving object detection method combining these two algorithms. When using Gaussian mixture model for modeling, improve the parts with differences, and keep the unmatched Gaussian distribution so that the modeling effect is similar to the actual background; the binary image is obtained through the difference between frames and the threshold, and the motion change domain is extracted through mathematical morphological filtering, and finally, the moving target is detected. The experiment proved the following: when there are more motion states, the recall rate is slightly better than that of the VIBE algorithm. It decreased about 0.05 or so, but the relative accuracy rate increased by about 0.12, and the increase ratio is significantly higher than the decrease ratio. Departments need to adopt effective target extraction methods. In order to improve the accuracy of moving target detection, this paper studies the method of background model establishment and target extraction and proposes its own improvement. (shrink)

This article proposes that the propagation of vibrations could serve as a better model for understanding the transmission of affect than the flow, circulation or movement of bodies by which it is most often theorized. The vibrations (or idiomatically ‘vibes’) among the sound system audience (or ‘crowd’) on a night out on the dancehall scene in Kingston, Jamaica, provide an example. Counting the repeating frequencies of these vibrations in a methodology inspired by Lefebvre’s rhythmanalysis results in a Frequency Spectrogram. This (...) ranges from the sociocultural frequencies of nightly, weekly and seasonal cycles and circulations of musical style and fashion, to the material frequencies of the amplitudes and timbres of sound itself, with reggae’s signature low-pitched bass-line, to the corporeal frequencies of the flesh and blood of the dancehall ‘crowd’, pulsating with heartbeats and kinetic dance rhythms. The vibration model then addresses the intensities of affect in terms of auditory amplitudes, as with sonic dominance; feelings as frequencies; and the distinctive meaning of affect as timbre. This aims to encourage the radical impulse of the idea of affect to abandon the traditional envelope of the autonomous, self-consistent, rational individual. The meaning of affect is thus located in the ratio, proportions and patterning of vibrations, that is, outside the discourse of emotions or representation of feelings. (shrink)

Seeking to expand on previous theories, this paper explores the AIR (Applying Intelligence to the Reflexes) approach to expert performance previously outlined by Geeves, Christensen, Sutton and McIlwain (2008). Data gathered from a semi-structured interview investigating the performance experience of Jeremy Kelshaw (JK), a professional musician, is explored. Although JK’s experience of music performance contains inherently uncertain elements, his phenomenological description of an ideal performance is tied to notions of vibe, connection and environment. The dynamic nature of music performance (...) advocated by the AIR approach is illustrated by the strategies that JK implements during performance. Through executing these strategies, JK attempts to increase the likelihood of vibe and connection by selectively exercising agency over performance variables within his control. In order to achieve this, JK must engage in ongoing monitoring of his performance, whereby the spotlight of his attention pans across a vast array of disparate performance processes (and levels within these processes) in order to ascertain how he can most effectively meet the specific demands of a given performance situation. It is hoped that future research compiling data from numerous interviews and sources as well as using different research methodologies will further unlock the potential that the AIR approach holds for understanding expert performance. (shrink)

Real-time smoke detection is of great significance for early warning of fire, which can avoid the serious loss caused by fire. Detecting smoke in actual scenes is still a challenging task due to large variance of smoke color, texture, and shapes. Moreover, the smoke detection in the actual scene is faced with the difficulties in data collection and insufficient smoke datasets, and the smoke morphology is susceptible to environmental influences. To improve the performance of smoke detection and solve the problem (...) of too few datasets in real scenes, this paper proposes a model that combines a deep convolutional generative adversarial network and a convolutional neural network to extract smoke features and detection. The vibe algorithm was used to collect smoke and nonsmoke images in the dynamic scene and deep convolutional generative adversarial network used these images to generate images that are as realistic as possible. Besides, we designed an improved convolutional neural network model for extracting smoke features and smoke detection. The experimental results show that the method has a good detection performance on the smoke generated in the actual scenes and effectively reduces the false alarm rate. (shrink)