Anchored deformable face ensemble alignment

At present, many approaches have been proposed for deformable face alignment with varying degrees of success. However, the common drawback to nearly all these approaches is the inaccurate landmark registrations. The registration errors which occur are predominantly heterogeneous (i.e. low error for some frames in a sequence and higher error for others). In this paper we propose an approach for simultaneously aligning an ensemble of deformable face images stemming from the same subject given noisy heterogeneous landmark estimates. We propose that these initial noisy landmark estimates can be used as an “anchor” in conjunction with known state-of-the-art objectives for unsupervised image ensemble alignment. Impressive alignment performance is obtained using well known deformable face fitting algorithms as “anchors.

Deformable face ensemble alignment with robust grouped-L1 anchors

Many methods exist at the moment for deformable face fitting. A drawback to nearly all these approaches is that they are (i) noisy in terms of landmark positions, and (ii) the noise is biased across frames (i.e. the misalignment is toward common directions across all frames). In this paper we propose a grouped $\mathcal{L}1$-norm anchored method for simultaneously aligning an ensemble of deformable face images stemming from the same subject, given noisy heterogeneous landmark estimates. Impressive alignment performance improvement and refinement is obtained using very weak initialization as "anchors".

Unsupervised temporal ensemble alignment for rapid annotation

This paper presents a novel framework for the unsupervised alignment of an ensemble of temporal sequences. This approach draws inspiration from the axiom that an ensemble of temporal signals stemming from the same source/class should have lower rank when "aligned" rather than "misaligned". Our approach shares similarities with recent state of the art methods for unsupervised images ensemble alignment (e.g. RASL) which breaks the problem into a set of image alignment problems (which have well known solutions i.e. the Lucas-Kanade algorithm). Similarly, we propose a strategy for decomposing the problem of temporal ensemble alignment into a similar set of independent sequence problems which we claim can be solved reliably through Dynamic Time Warping (DTW). We demonstrate the utility of our method using the Cohn-Kanade+ dataset, to align expression onset across multiple sequences, which allows us to automate the rapid discovery of event annotations.

Unsupervised alignment of thousands of images

The task addressed in this thesis is the automatic alignment of an ensemble of misaligned images in an unsupervised manner. This application is especially useful in computer vision applications where annotations of the shape of an object of interest present in a collection of images is required. Performing this task manually is a slow, tedious, expensive and error prone process which hinders the progress of research laboratories and businesses. Most recently, the unsupervised removal of geometric variation present in a collection of images has been referred to as congealing based on the seminal work of Learned-Miller [21]. The only assumption made in congealing is that the parametric nature of the misalignment is known a priori (e.g. translation, similarity, a�ne, etc) and that the object of interest is guaranteed to be present in each image. The capability to congeal an ensemble of misaligned images stemming from the same object class has numerous applications in object recognition, detection and tracking. This thesis concerns itself with the construction of a congealing algorithm titled, least-squares congealing, which is inspired by the well known image to image alignment algorithm developed by Lucas and Kanade [24]. The algorithm is shown to have superior performance characteristics when compared to previously established methods: canonical congealing by Learned-Miller [21] and stochastic congealing by Z�ollei [39].

Rank minimization across appearance and shape for AAM ensemble fitting

Active Appearance Models (AAMs) employ a paradigm of inverting a synthesis model of how an object can vary in terms of shape and appearance. As a result, the ability of AAMs to register an unseen object image is intrinsically linked to two factors. First, how well the synthesis model can reconstruct the object image. Second, the degrees of freedom in the model. Fewer degrees of freedom yield a higher likelihood of good fitting performance. In this paper we look at how these seemingly contrasting factors can complement one another for the problem of AAM fitting of an ensemble of images stemming from a constrained set (e.g. an ensemble of face images of the same person).

Mapping the evolution of optically generated rotational wave packets in a room-temperature ensemble of D2

A coherent superposition of rotational states in D2 has been excited by nonresonant, ultrafast (12 fs), intense (2×1014 W cm-2) 800 nm laser pulses, leading to impulsive dynamic alignment. Field-free evolution of this rotational wave packet has been mapped to high temporal resolution by a time-delayed pulse, initiating rapid double ionization, which is highly sensitive to the angle of orientation of the molecular axis with respect to the polarization direction, . The detailed fractional revivals of the neutral D2 wave packet as a function of and evolution time have been observed and modeled theoretically.

A statistical physics perspective on alignment-independent protein sequence comparison.

Motivation: Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function, and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly. Results: Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from “first passage probability distribution” to summarize statistics of ensemble averaged amino acid propensity values. In this paper, we introduce and elaborate this approach.

The necessary alignment between technology innovation effectiveness and operational effectiveness

Organisations are increasingly investing in complex technological innovations such as enterprise information systems with the aim of improving the operations of the business, and in this way gaining competitive advantage. However, the implementation of technological innovations tends to have an excessive focus on either technology innovation effectiveness (also known as system effectiveness), or the resulting operational effectiveness; focusing on either one of them is detrimental to the long-term enterprise benefits through failure to achieve the real value of technological innovations. The lack of research on the dimensions and performance objectives that organisations must be focusing on is the main reason for this misalignment. This research uses a combination of qualitative and quantitative, three-stage methodological approach. Initial findings suggest that factors such as quality of information from technology innovation effectiveness, and quality and speed from operational effectiveness are important and significantly well correlated factors that promote the alignment between technology innovation effectiveness and operational effectiveness.

Literature Review Value Alignment Process for Project Delivery

The objective of the project “Value Alignment Process for Project Delivery” is to provide a catalyst and tools for reform in the building and construction industry to transform business-as-usual performance into exceptional performance. The outcomes of this project will be beneficial to not only the construction industry, but to the community as a whole because a more sophisticated industry can deliver more effective use of assets, financing, operating and maintenance of facilities to suit the community’s needs. The research project consists of a study into best practice project delivery and the development of a suite of products, resources and services to guide project teams towards the best approach for a specific project. These resources will be focused on promoting the principles that underlie best practice project delivery, rather than on identifying a particular delivery system. The need for such tools and resources becomes more and more acute as the environment within which the construction industry operates becomes more and more complex, and as business and political imperatives shift to encompass or represent diverse stakeholder interests. To this end, this literature review looks at why it is essential to achieve transformation in the Australian construction industry in the context of its importance to the Australian economy. It seeks to investigate the concepts of ‘alignment’ and value’ as they pertain to construction industry processes and relationships. It comprehensively reviews drivers of project excellence and best practice project delivery principles and looks at how clients approach selection of project delivery systems. It critiques existing project delivery strategies and gives an overview of recent best practice initiatives. The literature review represents a milestone against the Project Agreement and forms a foundation document for this research project

Formative and summative assessment and the notion of constructive alignment

This paper discusses the different perceptions of first year accounting students about their tutorial activities and their engagements in assessment. As the literature suggests, unless participation in learning activities forms part of graded assessment, it is often difficult to engage students in these activities. Using an action research model, this paper reports the study of first year accounting students' responses to action-oriented learning tasks in tutorials. The paper focuses on the importance of aligning curriculum objectives, learning and teaching activities and assessment, i.e. the notion of constructive alignment. However, as the research findings indicate, without support at institutional level, applying constructive alignment to facilitate quality student learning outcomes is a difficult task. Thus, the impacts of policy constraints on curriculum issues are also discussed, focusing on the limitations faced by tutors and their lack of involvement in curriculum development.