Structured Knowledge Representation for Image Retrieval

We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing complex objects. As other approaches do, we start from low-level features extracted with image analysis to detect and characterize regions in an image. However, in contrast with feature-based approaches, we provide a syntax to describe segmented regions as basic objects and complex objects as compositions of basic ones. Then we introduce a companion extensional semantics for defining reasoning services, such as retrieval, classification, and subsumption. These services can be used for both exact and approximate matching, using similarity measures. Using our logical approach as a formal specification, we implemented a complete client-server image retrieval system, which allows a user to pose both queries by sketch and queries by example. A set of experiments has been carried out on a testbed of images to assess the retrieval capabilities of the system in comparison with expert users ranking. Results are presented adopting a well-established measure of quality borrowed from textual information retrieval

Impressionistic techniques applied in sound art & design

Sound art and design collectively refer to the process of specifying, acquiring, manipulating or generating sonic elements to evoke emotion and environment. Sound is used to convey the intentions, emotions, spirit or aura of a story, performance, or sonic installation. Sound connects unique aural environments, creating an immersive experience via mood and atmosphere. Impressionistic techniques such as Impasto, Pointillism, Sgraffito, Stippling introduced by 19th-century painters captured the essence of their subject in more vivid compositions, exuding authentic movements and atmosphere. This thesis applied impressionistic techniques using sound art and design to project specific mood and atmosphere responses among listeners. Four unique sound textures, each representing a technique from Impressionism, and a fifth composite sound texture were created for this project. All five sound textures were validated as representative of their respective Impressionistic technique. Only sonic Pointillism matched its emotive intent. This outcome supports the research question that sound art and design can be used to direct listeners’ mood and atmosphere responses. Partnering Impressionistic principles with sound art and design offers a deeper palette to sonically deliver more robust, holistic soundscapes for amplifying an audience’s listening experience. This project provides a foundation for future explorations and studies in applying cross-disciplinary artistic techniques with sound art and design or other artistic endeavors

Holistic facial composite systems: are they compatible with witness recall?

Facial composite systems offer a particular challenge to human-computer interaction as they must facilitate several cognitively complex tasks and also aid communication between the operator and the witness. This paper presents the findings from a survey conducted with UK police composite operators that explored some of the issues involved in composite construction. A particular emphasis was placed on the information that witnesses report and its compatibility with both the composite system interface and the underlying construction method used by the system

Perception Driven Texture Generation

This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or generation from procedural models. Generating textures from perceptual attributes have not been well studied yet. Meanwhile, perceptual attributes, such as directionality, regularity and roughness are important factors for human observers to describe a texture. In this paper, we propose a joint deep network model that combines adversarial training and perceptual feature regression for texture generation, while only random noise and user-defined perceptual attributes are required as input. In this model, a preliminary trained convolutional neural network is essentially integrated with the adversarial framework, which can drive the generated textures to possess given perceptual attributes. An important aspect of the proposed model is that, if we change one of the input perceptual features, the corresponding appearance of the generated textures will also be changed. We design several experiments to validate the effectiveness of the proposed method. The results show that the proposed method can produce high quality texture images with desired perceptual properties.Comment: 7 pages, 4 figures, icme201

The composite first person narrative: Texture, structure, and meaning in writing phenomenological descriptions

This paper illustrates the use of composite first person narrative interpretive methods, as described by Todres, across a range of phenomena. This methodology introduces texture into the presently understood structures of phenomena and thereby creates new understandings of the phenomenon, bringing about a form of understanding that is relationally alive that contributes to improved caring practices. The method is influenced by the work of Gendlin, Heidegger, van Manen, Gadamer, and Merleau-Ponty. The method's applicability to different research topics is demonstrated through the composite narratives of nursing students learning nursing practice in an accelerated and condensed program, obese female adolescents attempting weight control, chronically ill male parolees, and midlife women experiencing distress during menopause. Within current research, these four phenomena have been predominantly described and understood through quantified articulations that give the reader a structural understanding of the phenomena, but the more embodied or “contextual” human qualities of the phenomena are often not visible. The “what is it like” or the “unsaid” aspects of such human phenomena are not clear to the reader when proxies are used to “account for” a variety of situated conditions. This novel method is employed to re-present narrative data and findings from research through first person accounts that blend the voices of the participants with those of the researcher, emphasizing the connectedness, the “we” among all participants, researchers, and listeners. These re-presentations allow readers to develop more embodied understandings of both the texture and structure of each of the phenomena and illustrate the use of the composite account as a way for researchers to better understand and convey the wholeness of the experience of any phenomenon under inquiry

Models of incremental concept formation

Given a set of observations, humans acquire concepts that organize those observations and use them in classifying future experiences. This type of concept formation can occur in the absence of a tutor and it can take place despite irrelevant and incomplete information. A reasonable model of such human concept learning should be both incremental and capable of handling this type of complex experiences that people encounter in the real world. In this paper, we review three previous models of incremental concept formation and then present CLASSIT, a model that extends these earlier systems. All of the models integrate the process of recognition and learning, and all can be viewed as carrying out search through the space of possible concept hierarchies. In an attempt to show that CLASSIT is a robust concept formation system, we also present some empirical studies of its behavior under a variety of conditions

Dynamic wetting and spreading and the role of topography

Hoffman-de Gennes law, which relates the edge speed, ve, to the dynamic and equilibrium contact angles q and qe by ve µq(q2 -qe 2 ). When the liquid wets the surface completely and the equilibrium contact angle vanishes, the edge speed is proportional to the cube of the dynamic contact angle. When the droplets are non-volatile this law gives rise to simple power laws with time for the contact angle and other parameters in both the capillary and gravity dominated regimes. On a textured surface the equilibrium state of a droplet is strongly modified due to the amplification of the surface chemistry induced tendencies by the topography. The most common example is the conversion of hydrophobicity into superhydrophobicity. However, when the surface chemistry favors partial wetting, topography can result in a droplet spreading completely. A further, frequently over-looked consequence of topography is that the rate at which an out-of-equilibrium droplet spreads should also be modified. In this report, we review ideas related to the idea of topography induced wetting and consider how this may relate to dynamic wetting and the rate of droplet spreading. We consider the effect of the Wenzel and Cassie-Baxter equations on the driving forces and discuss how these may modify power-laws for spreading. We relate the ideas to both the hydrodynamic viscous dissipation model and the molecular-kinetic theory of spreading. This suggests roughness and solid surface fraction modified Hoffman-de Gennes laws relating the edge speed to the dynamic and equilibrium contact angle

The analysis of facial beauty: an emerging area of research in pattern analysis

Much research presented recently supports the idea that the human perception of attractiveness is data-driven and largely irrespective of the perceiver. This suggests using pattern analysis techniques for beauty analysis. Several scientific papers on this subject are appearing in image processing, computer vision and pattern analysis contexts, or use techniques of these areas. In this paper, we will survey the recent studies on automatic analysis of facial beauty, and discuss research lines and practical application