Scottish Archaeological Research Framework: Future Thinking on Carved Stones

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Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking

Object-to-camera motion produces a variety of apparent motion patterns that significantly affect performance of short-term visual trackers. Despite being crucial for designing robust trackers, their influence is poorly explored in standard benchmarks due to weakly defined, biased and overlapping attribute annotations. In this paper we propose to go beyond pre-recorded benchmarks with post-hoc annotations by presenting an approach that utilizes omnidirectional videos to generate realistic, consistently annotated, short-term tracking scenarios with exactly parameterized motion patterns. We have created an evaluation system, constructed a fully annotated dataset of omnidirectional videos and the generators for typical motion patterns. We provide an in-depth analysis of major tracking paradigms which is complementary to the standard benchmarks and confirms the expressiveness of our evaluation approach

Co-Operation with Users: Challenges from (I)Literacy and Cultures

With the developments in the global market, designs focusing on the users of Information Technologies becomes a competitive factor since successful diffusion and up-take of IT lie with the users. But users have different IT competences and are culturally different. These are challenges that HCI-design methodologies need to address. User-Centred Design offers a possible approach but there are limitations that must be dealt with to strengthen user oriented and interdisciplinary approaches, and the development of techniques and tools that are suitable for handling the complexity of designing for a global world. This research-in-progress paper outlines preliminary reflections on – and contributions to – the development and qualification of techniques and tools that address user-centred design in a global context. We discuss User-Centred Design and qualify this approach by aligning with the Scandinavian IS tradition of co-operating directly with users. We suggest an approach inspired by the Scandinavian approach to IS design as a possible point of departure for targeting global users. We introduce the conceptual and experimental work in our Vision Lab, an approach based on co-operation with users and on the fundamental understanding of design methods as a relational practice that takes place between objects, contexts, users, and designers. We describe different techniques we have explored, characterized by giving the users voice throughout the design effort. In a final chapter we re-address the global perspective, and point out that virtual co-operation with the users is the next challenge. We suggest two digital techniques which may be explored for virtual cooperative design, discuss potential challenges to these methods, and conclude with propositions for further research to be carried out in the Vision Lab

Multi-Source Neural Variational Inference

Learning from multiple sources of information is an important problem in machine-learning research. The key challenges are learning representations and formulating inference methods that take into account the complementarity and redundancy of various information sources. In this paper we formulate a variational autoencoder based multi-source learning framework in which each encoder is conditioned on a different information source. This allows us to relate the sources via the shared latent variables by computing divergence measures between individual source's posterior approximations. We explore a variety of options to learn these encoders and to integrate the beliefs they compute into a consistent posterior approximation. We visualise learned beliefs on a toy dataset and evaluate our methods for learning shared representations and structured output prediction, showing trade-offs of learning separate encoders for each information source. Furthermore, we demonstrate how conflict detection and redundancy can increase robustness of inference in a multi-source setting.Comment: AAAI 2019, Association for the Advancement of Artificial Intelligence (AAAI) 201

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presentedSiirretty Doriast

Archaeoentomological Research in the North Atlantic : Past, Present, and Future

Peer reviewedPublisher PD

A comparative analysis of binary patterns with discrete cosine transform for gender classification

This paper presents a comparative analysis of binary patters for gender classification with a novel method of feature transformation for improved accuracy rates. The main requirements of our application are speed and accuracy. We investigate a combination of local binary patterns (LBP), Census Transform (CT) and Modified Census Transform (MCT) applied over the full, top and bottom halves of the face. Gender classification is performed using support vector machines (SVM). A main focus of the investigation is to determine whether or not a 1D discrete cosine transform (DCT) applied directly to the grey level histograms would improve accuracy. We used a public database of faces and run face and eye detection algorithms allowing automatic cropping and normalisation of the images. A set of 120 tests over the entire database demonstrate that the proposed 1D discrete cosine transform improves accuracy in all test cases with small standard deviations. It is shown that using basic versions of the algorithms, LBP is marginally superior to both CT and MCT and agrees with results in the literature for higher accuracy on male subjects. However, a significant result of our investigation is that, by applying a 1D-DCT this bias is removed and an equivalent error rate is achieved for both genders. Furthermore, it is demonstrated that DCT improves overall accuracy and renders CT a superior performance compared to LBP in all cases considered