Visual route recognition with a handful of bits

In this paper we use a sequence-based visual localization algorithm to reveal surprising answers to the question, how much visual information is actually needed to conduct effective navigation? The algorithm actively searches for the best local image matches within a sliding window of short route segments or 'sub-routes', and matches sub-routes by searching for coherent sequences of local image matches. In contract to many existing techniques, the technique requires no pre-training or camera parameter calibration. We compare the algorithm's performance to the state-of-the-art FAB-MAP 2.0 algorithm on a 70 km benchmark dataset. Performance matches or exceeds the state of the art feature-based localization technique using images as small as 4 pixels, fields of view reduced by a factor of 250, and pixel bit depths reduced to 2 bits. We present further results demonstrating the system localizing in an office environment with near 100% precision using two 7 bit Lego light sensors, as well as using 16 and 32 pixel images from a motorbike race and a mountain rally car stage. By demonstrating how little image information is required to achieve localization along a route, we hope to stimulate future 'low fidelity' approaches to visual navigation that complement probabilistic feature-based techniques.

Built to last versus meant to end : time bounds specification in strategic alliances

This article explores an important temporal aspect of the design of strategic alliances by focusing on the issue of time bounds specification. Time bounds specification refers to a choice on behalf of prospective alliance partners at the time of alliance formation to either pre-specify the duration of an alliance to a specific time window, or to keep the alliance open-ended (Reuer & Ariňo, 2007). For instance, Das (2006) mentions the example of the alliance between Telemundo Network and Mexican Argos Comunicacion (MAC). Announced in October 2000, this alliance entailed a joint production of 1200 hours of comedy, news, drama, reality and novella programs (Das, 2006). Conditioned on the projected date of completing the 1200 hours of programs, Telemundo Network and MAC pre-specified the time bounds of the alliance ex ante. Such time-bound alliances are said to be particularly prevalent in project-based industries, like movie production, construction, telecommunications and pharmaceuticals (Schwab & Miner, 2008). In many other instances, however, firms may choose to keep their alliances open-ended, not specifying a specific time bound at the time of alliance formation. The choice between designing open-ended alliances that are “built to last”, versus time bound alliances that are “meant to end” is important. Seminal works like Axelrod (1984), Heide & Miner (1992), and Parkhe (1993) demonstrated that the choice to place temporal bounds on a collaborative venture has important implications. More specifically, collaborations that have explicit, short term time bounds (i.e. what is termed a shorter “shadow of the future”) are more likely to experience opportunism (Axelrod, 1984), are more likely to focus on the immediate present (Bakker, Boros, Kenis & Oerlemans, 2012), and are less likely to develop trust (Parkhe, 1993) than alliances for which time bounds are kept indeterminate. These factors, in turn, have been shown to have important implications for the performance of alliances (e.g. Kale, Singh & Perlmutter, 2000). Thus, there seems to be a strong incentive for organizations to form open-ended strategic alliances. And yet, Reuer & Ariňo (2007), one of few empirical studies that details the prevalence of time-bound and open-ended strategic alliances, found that about half (47%) of the alliances in their sample were time bound, the other half were open-ended. What conditions, then, determine this choice?

Silk fibroin in ocular surface reconstruction : what is its potential as a biomaterial in ophthalmics?

Hardly a month goes by within the scientific literature without some new material “X” being reported as a suitable material on which to grow cell type “Y”, for the potential purpose of treating disease “Z”. Thus when fibroin, a protein found in silk, was first proposed as a biomaterial for cell growth [1] it joined a long list of other materials of both natural as well as synthetic origin. Nevertheless, in the second decade of the Asian Century it is perhaps befitting that a material of so much importance to the continent’s cultural and economic history, should become the focus of cutting-edge biomedical research. Sentiments aside, however, silk fibroin possesses quite a unique combination of properties which make it a promising candidate for repairing the eye and especially for treating damage to the cornea, the transparent window at the front of the eye.

Health complaint commissions in Australia : time for a national approach to data collection

Health complaint statistics are important for identifying problems and bringing about improvements to health care provided by health service providers and to the wider health care system. This paper overviews complaints handling by the eight Australian state and territory health complaint entities, based on an analysis of data from their annual reports. The analysis shows considerable variation between jurisdictions in the ways complaint data are defined, collected and recorded. Complaints from the public are an important accountability mechanism and open a window on service quality. The lack of a national approach leads to fragmentation of complaint data and a lost opportunity to use national data to assist policy development and identify the main areas causing consumers to complain. We need a national approach to complaints data collection in order to better respond to patients’ concerns.

Passenger transmission and productiveness of transit lines with high loads

Deterministic transit capacity analysis applies to planning, design and operational management of urban transit systems. The Transit Capacity and Quality of Service Manual (1) and Vuchic (2, 3) enable transit performance to be quantified and assessed using transit capacity and productive capacity. This paper further defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures the transit task performed over distance. Passenger transmission (p-km/h) captures the passenger task delivered by service at speed. Transit productiveness (p-km/h) captures transit work performed over time. These measures are useful to operators in understanding their services’ or systems’ capabilities and passenger quality of service. This paper accounts for variability in utilized demand by passengers along a line and high passenger load conditions where passenger pass-up delay occurs. A hypothetical case study of an individual bus service’s operation demonstrates the usefulness of passenger transmission in comparing existing and growth scenarios. A hypothetical case study of a bus line’s operation during a peak hour window demonstrates the theory’s usefulness in examining the contribution of individual services to line productive performance. Scenarios may be assessed using this theory to benchmark or compare lines and segments, conditions, or consider improvements.

An extension to the rank constraint for improving the reliability of stereo matching algorithms using the rank transform

The rank transform is one non-parametric transform which has been applied to the stereo matching problem The advantages of this transform include its invariance to radio metric distortion and its amenability to hardware implementation. This paper describes the derivation of the rank constraint for matching using the rank transform Previous work has shown that this constraint was capable of resolving ambiguous matches thereby improving match reliability A new matching algorithm incorporating this constraint was also proposed. This paper extends on this previous work by proposing a matching algorithm which uses a dimensional match surface in which the match score is computed for every possible template and match window combination. The principal advantage of this algorithm is that the use of the match surface enforces the left�right consistency and uniqueness constraints thus improving the algorithms ability to remove invalid matches Experimental results for a number of test stereo pairs show that the new algorithm is capable of identifying and removing a large number of in incorrect matches particularly in the case of occlusions

Estimating the probability of an invalid match for matching using the rank transform

A fundamental problem faced by stereo matching algorithms is the matching or correspondence problem. A wide range of algorithms have been proposed for the correspondence problem. For all matching algorithms, it would be useful to be able to compute a measure of the probability of correctness, or reliability of a match. This paper focuses in particular on one class for matching algorithms, which are based on the rank transform. The interest in these algorithms for stereo matching stems from their invariance to radiometric distortion, and their amenability to fast hardware implementation. This work differs from previous work in that it derives, from first principles, an expression for the probability of a correct match. This method was based on an enumeration of all possible symbols for matching. The theoretical results for disparity error prediction, obtained using this method, were found to agree well with experimental results. However, disadvantages of the technique developed in this chapter are that it is not easily applicable to real images, and also that it is too computationally expensive for practical window sizes. Nevertheless, the exercise provides an interesting and novel analysis of match reliability.

Architecture post mortem : the diastolic architecture of decline, dystopia, and death

Architecture Post Mortem surveys architecture’s encounter with death, decline, and ruination following late capitalism. As the world moves closer to an economic abyss that many perceive to be the death of capital, contraction and crisis are no longer mere phases of normal market fluctuations, but rather the irruption of the unconscious of ideology itself. Post mortem is that historical moment wherein architecture’s symbolic contract with capital is put on stage, naked to all. Architecture is not irrelevant to fiscal and political contagion as is commonly believed; it is the victim and penetrating analytical agent of the current crisis. As the very apparatus for modernity’s guilt and unfulfilled drives-modernity’s debt-architecture is that ideological element that functions as a master signifier of its own destruction, ordering all other signifiers and modes of signification beneath it. It is under these conditions that architecture theory has retreated to an “Alamo” of history, a final desert outpost where history has been asked to transcend itself. For architecture’s hoped-for utopia always involves an apocalypse. This timely collection of essays reformulates architecture’s relation to modernity via the operational death-drive: architecture is but a passage between life and death. This collection includes essays by Kazi K. Ashraf, David Bertolini, Simone Brott, Peggy Deamer, Didem Ekici, Paul Emmons, Donald Kunze, Todd McGowan, Gevork Hartoonian, Nadir Lahiji, Erika Naginski, and Dennis Maher. Contents: Introduction: ‘the way things are’, Donald Kunze; Driven into the public: the psychic constitution of space, Todd McGowan; Dead or alive in Joburg, Simone Brott; Building in-between the two deaths: a post mortem manifesto, Nadir Lahiji; Kant, Sade, ethics and architecture, David Bertolini; Post mortem: building deconstruction, Kazi K. Ashraf; The slow-fast architecture of love in the ruins, Donald Kunze; Progress: re-building the ruins of architecture, Gevork Hartoonian; Adrian Stokes: surface suicide, Peggy Deamer; A window to the soul: depth in the early modern section drawing, Paul Emmons; Preliminary thoughts on Piranesi and Vico, Erika Naginski; architectural asceticism and austerity, Didem Ekici; 900 miles to Paradise, and other afterlives of architecture, Dennis Maher; Index.

Automatic Audio Segmentation Using the Generalized Likelihood Ratio

This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.

Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

Static analysis of executables for collaborative malware detection on Android

Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. As smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the corresponding resource constraints. The contribution of this paper is twofold. First, we perform static analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach to extend these results. Corresponding simulation results are presented.

Collective sampling and analysis of high order tensors for chatroom communications

This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

Visualising security incidents through event aggregation

Extracting and aggregating the relevant event records relating to an identified security incident from the multitude of heterogeneous logs in an enterprise network is a difficult challenge. Presenting the information in a meaningful way is an additional challenge. This paper looks at solutions to this problem by first identifying three main transforms; log collection, correlation, and visual transformation. Having identified that the CEE project will address the first transform, this paper focuses on the second, while the third is left for future work. To aggregate by correlating event records we demonstrate the use of two correlation methods, simple and composite. These make use of a defined mapping schema and confidence values to dynamically query the normalised dataset and to constrain result events to within a time window. Doing so improves the quality of results, required for the iterative re-querying process being undertaken. Final results of the process are output as nodes and edges suitable for presentation as a network graph.

Speaker diarization : "who spoke when"

Speaker diarization is the process of annotating an input audio with information that attributes temporal regions of the audio signal to their respective sources, which may include both speech and non-speech events. For speech regions, the diarization system also specifies the locations of speaker boundaries and assign relative speaker labels to each homogeneous segment of speech. In short, speaker diarization systems effectively answer the question of ‘who spoke when’. There are several important applications for speaker diarization technology, such as facilitating speaker indexing systems to allow users to directly access the relevant segments of interest within a given audio, and assisting with other downstream processes such as summarizing and parsing. When combined with automatic speech recognition (ASR) systems, the metadata extracted from a speaker diarization system can provide complementary information for ASR transcripts including the location of speaker turns and relative speaker segment labels, making the transcripts more readable. Speaker diarization output can also be used to localize the instances of specific speakers to pool data for model adaptation, which in turn boosts transcription accuracies. Speaker diarization therefore plays an important role as a preliminary step in automatic transcription of audio data. The aim of this work is to improve the usefulness and practicality of speaker diarization technology, through the reduction of diarization error rates. In particular, this research is focused on the segmentation and clustering stages within a diarization system. Although particular emphasis is placed on the broadcast news audio domain and systems developed throughout this work are also trained and tested on broadcast news data, the techniques proposed in this dissertation are also applicable to other domains including telephone conversations and meetings audio. Three main research themes were pursued: heuristic rules for speaker segmentation, modelling uncertainty in speaker model estimates, and modelling uncertainty in eigenvoice speaker modelling. The use of heuristic approaches for the speaker segmentation task was first investigated, with emphasis placed on minimizing missed boundary detections. A set of heuristic rules was proposed, to govern the detection and heuristic selection of candidate speaker segment boundaries. A second pass, using the same heuristic algorithm with a smaller window, was also proposed with the aim of improving detection of boundaries around short speaker segments. Compared to single threshold based methods, the proposed heuristic approach was shown to provide improved segmentation performance, leading to a reduction in the overall diarization error rate. Methods to model the uncertainty in speaker model estimates were developed, to address the difficulties associated with making segmentation and clustering decisions with limited data in the speaker segments. The Bayes factor, derived specifically for multivariate Gaussian speaker modelling, was introduced to account for the uncertainty of the speaker model estimates. The use of the Bayes factor also enabled the incorporation of prior information regarding the audio to aid segmentation and clustering decisions. The idea of modelling uncertainty in speaker model estimates was also extended to the eigenvoice speaker modelling framework for the speaker clustering task. Building on the application of Bayesian approaches to the speaker diarization problem, the proposed approach takes into account the uncertainty associated with the explicit estimation of the speaker factors. The proposed decision criteria, based on Bayesian theory, was shown to generally outperform their non- Bayesian counterparts.

Guitar

Poem