The politics and poetics of coexistence : experiments at the intersection of art and environmental engineering

This research project explores how interdisciplinary art practices can provide ways for questioning and envisaging alternative modes of coexistence between humans and the non-humans who together, make up the environment. As a practiceled project, it combines a body of creative work (50%) and this exegesis (50%). My interdisciplinary artistic practice appropriates methods and processes from science and engineering and merges them into artistic contexts for critical and poetic ends. By blending pseudo-scientific experimentation with creative strategies like visual fiction, humour, absurd public performance and scripted audience participation, my work engages with a range of debates around ecology. This exegesis details the interplay between critical theory relating to these debates, the work of other creative practitioners and my own evolving artistic practice. Through utilising methods and processes drawn from my prior career in water engineering, I present an interdisciplinary synthesis that seeks to promote improved understandings of the causes and consequences of our ecological actions and inactions.

Constructing the shitting citizen : the promise of scatological art as environmental and social activism

Art activism uses visual and performance art to promote social and environmental agendas. In this paper, I explore attempts to raise awareness of sanitation issues at the global, local and personal level using scatological art. I focus on the successes of the open-air public art exhibition set up in the Brisbane (Queensland, Australia) central business district to celebrate World Toilet Day in 2008. The art in this exhibition featured included one hundred toilets decorated to raise awareness of global sanitation issues and the distribution of promotional materials featuring scatological images including postcards and stickers. Given the subject matter and intent, the toilet art and promotional materials presented at the One Hundred Toilet exhibition can be seen as an example of scatological art employed for the purposes of social and environmental activism. Through the One Hundred Toilet exhibition, I consider the political aims and activist potential of using scatological art to progress social and environmental agendas and consider how this kind of ‘shit on show’ approach can contribute to the construction of the shitting citizen; one who is simultaneously responsible for and responsive to managing the waste that they produce and recognising and responding to broader sanitation issues.

Looking into the light : reinventing the apparatus in contemporary art

Technical images such as photography, film and video, are dependent on apparatuses for their production and dissemination, yet the apparatus itself is often hidden or obscured in the experience of the work and the discourse that surrounds it. This practice-led research identifies key practice strategies to foreground the apparatus both in the production of work and in its presentation. It therefore develops critical and generative strategies to explore and interrogate the workings of the 'apparatus-audience complex,' and the particular modes of spectatorship that this entails.

Knitted images : drawing patterns

This Arts Based Education Research (Eisner 2008) work provides potent opportunity to consider different problems and challenges that impact on the progress of research (art as data making) and the theories being explored. It provides opportunity to transport ideas across between research activity, and teaching practices...

Unsupervised online learning of condition-invariant images for place recognition

This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

CCD: Connected Component Descriptor for Robust Mosaicing of Camera-Captured Document Images

We propose a robust method for mosaicing of document images using features derived from connected components. Each connected component is described using the Angular Radial Tran. form (ART). To ensure geometric consistency during feature matching, the ART coefficients of a connected component are augmented with those of its two nearest neighbors. The proposed method addresses two critical issues often encountered in correspondence matching: (i) The stability of features and (ii) Robustness against false matches due to the multiple instances of characters in a document image. The use of connected components guarantees a stable localization across images. The augmented features ensure a successful correspondence matching even in the presence of multiple similar regions within the page. We illustrate the effectiveness of the proposed method on camera captured document images exhibiting large variations in viewpoint, illumination and scale.

Mediated music makers : Constructing author images in popular music

The subject of the thesis is the mediated construction of author images in popular music. In the study, the construction of images is treated as a process in which artists, the media and the members of the audience participate. The notions of presented, mediated and compiled author images are used in explaining the mediation process and the various authorial roles of the agents involved. In order to explore the issue more closely, I analyse the author images of a group of popular music artists representing the genres of rock, pop and electronic dance music. The analysed material consists mostly of written media texts through which the artists authorial roles and creative responsibilities are discussed. Theoretically speaking, the starting points for the examination lie in cultural studies and discourse analysis. Even though author images may be conceived as intertextual constructions, the artist is usually presented as a recognizable figure whose purpose is to give the music its public face. This study does not, then, deal with musical authors as such, but rather with their public images and mediated constructions. Because of the author-based functioning of popular music culture and the idea of the artist s individual creative power, the collective and social processes involved in the making of popular music are often superseded by the belief in a single, originating authorship. In addition to the collective practices of music making, the roles of the media and the marketing machinery complicate attempts to clarify the sharing of authorial contributions. As the case studies demonstrate, the differences between the examined author images are connected with a number of themes ranging from issues of auteurism and stardom to the use of masked imagery and the blending of authorial voices. Also the emergence of new music technologies has affected not only the ways in which music is made, but also how the artist s authorial status and artistic identity is understood. In the study at hand, the author images of auteurs, stars, DJs and sampling artists are discussed alongside such varied topics as collective authorship, evaluative hierarchies, visual promotion and generic conventions. Taken altogether, the examined case studies shed light on the functioning of popular music culture and the ways in which musical authorship is (re)defined.

Vykopirovka s plana Seĭtlerskoĭ dachi razverstani︠ia︡, Kr.A.S.SD.R., na uchastok zemli otvedennyĭ KOMZET'u (s -Kh. ART. "Rabotnik" - Aranda), pri provedenii rabot po zemreforme v 1930 g.

Digital image

Vykopirovka s plana Seĭtlerskoǐ dachi razverstani︠ia︡ Kr.A.S.SD.R., na uchastok zemli otvedennyĭ KOMZET'u (s.-kh. art. "Vozrazhdenie" - Krasn. Burlak), pri provedenii rabot po zemreforme v 1930 g.

Digital image

Real-time image denoising algorithm in teleradiology systems - art.no.606304

Denoising of medical images in wavelet domain has potential application in transmission technologies such as teleradiology. This technique becomes all the more attractive when we consider the progressive transmission in a teleradiology system. The transmitted images are corrupted mainly due to noisy channels. In this paper, we present a new real time image denoising scheme based on limited restoration of bit-planes of wavelet coefficients. The proposed scheme exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each sub-band. The desired bit-rate control is achieved by applying the restoration on a limited number of bit-planes subject to the optimal smoothing. The proposed method adapts itself to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with unrestored case, in context of error reduction. It also has capability to adapt to situations where noise level in the image varies and with the changing requirements of medical-experts. The applicability of the proposed approach has implications in restoration of medical images in teleradiology systems. The proposed scheme is computationally efficient.

Novel composite coded pattern for small angle measurement using imaging method -art.no.62891D

A novel approach for measurement of small rotation angles using imaging method is proposed and demonstrated. A plane mirror placed on a precision rotating table is used for imaging the newly designed composite coded pattern. The imaged patterns are captured with the help of a CCD camera. The angular rotation of the plane mirror is determined from a pair of the images of the pattern, captured once before and once after affecting the tilt of the mirror. Both simulation and experimental results suggest that the proposed approach not only retains the advantages of the original imaging method but also contributes significantly to the enhancement of its measuring range (+/- 4.13 degrees with accuracy of the order of 1 arcsec).

Elimination of cross-talk in diffuse optical tomographic reconstructions through a weighted update procedure: results of simulation study - art. no. 61640S

Reconstructions in optical tomography involve obtaining the images of absorption and reduced scattering coefficients. The integrated intensity data has greater sensitivity to absorption coefficient variations than scattering coefficient. However, the sensitivity of intensity data to scattering coefficient is not zero. We considered an object with two inhomogeneities (one in absorption and the other in scattering coefficient). The standard iterative reconstruction techniques produced results, which were plagued by cross talk, i.e., the absorption coefficient reconstruction has a false positive corresponding to the location of scattering inhomogeneity, and vice-versa. We present a method to remove cross talk in the reconstruction, by generating a weight matrix and weighting the update vector during the iteration. The weight matrix is created by the following method: we first perform a simple backprojection of the difference between the experimental and corresponding homogeneous intensity data. The built up image has greater weightage towards absorption inhomogeneity than the scattering inhomogeneity and its appropriate inverse is weighted towards the scattering inhomogeneity. These two weight matrices are used as multiplication factors in the update vectors, normalized backprojected image of difference intensity for absorption inhomogeneity and the inverse of the above for the scattering inhomogeneity, during the image reconstruction procedure. We demonstrate through numerical simulations, that cross-talk is fully eliminated through this modified reconstruction procedure.

Exploring Transfer Learning Approaches for Head Pose Classification from Multi-view Surveillance Images

Head pose classification from surveillance images acquired with distant, large field-of-view cameras is difficult as faces are captured at low-resolution and have a blurred appearance. Domain adaptation approaches are useful for transferring knowledge from the training (source) to the test (target) data when they have different attributes, minimizing target data labeling efforts in the process. This paper examines the use of transfer learning for efficient multi-view head pose classification with minimal target training data under three challenging situations: (i) where the range of head poses in the source and target images is different, (ii) where source images capture a stationary person while target images capture a moving person whose facial appearance varies under motion due to changing perspective, scale and (iii) a combination of (i) and (ii). On the whole, the presented methods represent novel transfer learning solutions employed in the context of multi-view head pose classification. We demonstrate that the proposed solutions considerably outperform the state-of-the-art through extensive experimental validation. Finally, the DPOSE dataset compiled for benchmarking head pose classification performance with moving persons, and to aid behavioral understanding applications is presented in this work.

Patch-based and multiresolution optimum bilateral filters for denoising images corrupted by Gaussian noise

We propose optimal bilateral filtering techniques for Gaussian noise suppression in images. To achieve maximum denoising performance via optimal filter parameter selection, we adopt Stein's unbiased risk estimate (SURE)-an unbiased estimate of the mean-squared error (MSE). Unlike MSE, SURE is independent of the ground truth and can be used in practical scenarios where the ground truth is unavailable. In our recent work, we derived SURE expressions in the context of the bilateral filter and proposed SURE-optimal bilateral filter (SOBF). We selected the optimal parameters of SOBF using the SURE criterion. To further improve the denoising performance of SOBF, we propose variants of SOBF, namely, SURE-optimal multiresolution bilateral filter (SMBF), which involves optimal bilateral filtering in a wavelet framework, and SURE-optimal patch-based bilateral filter (SPBF), where the bilateral filter parameters are optimized on small image patches. Using SURE guarantees automated parameter selection. The multiresolution and localized denoising in SMBF and SPBF, respectively, yield superior denoising performance when compared with the globally optimal SOBF. Experimental validations and comparisons show that the proposed denoisers perform on par with some state-of-the-art denoising techniques. (C) 2015 SPIE and IS&T