Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Affecting interference

This collaborative project by Daniel Mafe and Andrew Brown, one of a number in they have been involved in together, conjoins painting and digital sound into a single, large scale, immersive exhibition/installation. The work as a whole acts as an interstitial point between contrasting approaches to abstraction: the visual and aural, the digital and analogue are pushed into an alliance and each works to alter perceptions of the other. For example, the paintings no longer mutely sit on the wall to be stared into. The sound seemingly emanating from each work shifts the viewer’s typical visual perception and engages their aural sensibilities. This seems to make one more aware of the objects as objects – the surface of each piece is brought into scrutiny – and immerses the viewer more viscerally within the exhibition. Similarly, the sonic experience is focused and concentrated spatially by each painted piece even as the exhibition is dispersed throughout the space. The sounds and images are similar in each local but not identical, even though they may seem to be the same from casual interaction, closer attention will quickly show this is not the case. In preparing this exhibition each artist has had to shift their mode of making to accommodate the other’s contribution. This was mainly done by a process of emptying whereby each was called upon to do less to the works they were making and to iterate the works toward a shared conception, blurring notions of individual imagination while maintaining material authorship. Empting was necessary to enable sufficient porosity where each medium allowed the other entry to its previously gated domain. The paintings are simple and subtle to allow the odd sonic textures a chance to work on the viewer’s engagement with them. The sound remains both abstract, using noise-like textures, and at a low volume to allow the audience’s attention to wander back and forth between aspects of the works.

The role of randomly mixed-layered chlorite/smectite in the transformation of smectite to chlorite

Vesicular and groundmass phyllosilicates in a hydrothermally altered basalt from the Point Sal ophiolite, California, have been studied using transmission electron microscopy (TEM). Pore-filling phyllosilicates are texturally characterized as having coherent, relatively thick and defect-free crystals of chlorite (14 Å) with occasional 24-Å periodicities. Groundmass phyllosilicates are texturally characterized as 1) randomly oriented crystals up to 200 Å in width and 2) larger, more coherent crystals up to 1000 Å in width. Small crystallites contain predominantly 14-Å layers with some 24-Å units. Large crystals show randomly interlayered chlorite/smectite (C/S), with approximately 50% chlorite on average. Adjacent smectite-like layers are not uncommon in the groundmass phyllosilicates. Electron microprobe analyses show that Fe/Mg ratios of both groundmass and vesicular phyllosilicates are fairly constant. Termination of brucite-like interlayers has been identified in some of the TEM images. The transformation mechanisms represented by these layer terminations are 1) growth of a brucite-like interlayer within smectite interlayer regions and 2) the dissolution and reprecipitation of elements to form chlorite layers. Both mechanisms require an increase in volume as smectite transforms to chlorite. The data, combined with that from previously published reports, suggest that randomly interlayered C/S is a metastable phase formed in microenvironments with low water/rock ratios. Chlorite forms in microenvironments in the same sample dominated by higher water/rock ratios. The relatively constant number of Mg's in the structure (Mg#) of both structures indicates that in both microenvironments the bulk rock composition has influence over the composition of phyllosilicates.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Abstract: Texture enhancement is an important component of image processing, with extensive application in science and engineering. The quality of medical images, quantified using the texture of the images, plays a significant role in the routine diagnosis performed by medical practitioners. Previously, image texture enhancement was performed using classical integral order differential mask operators. Recently, first order fractional differential operators were implemented to enhance images. Experiments conclude that the use of the fractional differential not only maintains the low frequency contour features in the smooth areas of the image, but also nonlinearly enhances edges and textures corresponding to high-frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we applied the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other fractional differential operators, our new algorithms provide higher signal to noise values, which leads to superior image quality.

Flexural and shear bond characteristics of thin layer polymer cement mortared concrete masonry

This paper presents an experimental investigation of the flexural and shear bond characteristics of thin layer polymer cement mortared concrete masonry. It is well known that the bond characteristics of masonry depend upon the mortar type, the techniques of dispersion of mortar and the surface texture of concrete blocks; there exists an abundance of literature on the conventional 10 mm thick cement mortared masonry bond; however, 1-4 mm thick polymer cement mortared masonry bond is not yet well researched. This paper reports a study on the examination of the effect of mortar compositions, dispersion methods and unit surface textures to the flexural and shear bond characteristics of thin layer mortared concrete masonry. A non-contact digital image correlation method was adopted for the measurement of strains at the unit-mortar interface in this research. All mortar joints have been carefully prepared to ensure achievement of the desired thin layer mortar thickness on average. The results exhibit that the bond strength of thin mortar layered concrete masonry with polymer cement mortar is higher than that of the conventional masonry; moreover the unit surface texture and the mortar dispersion methods are found to have significant influence on the flexural and shear bond characteristics. From the experimental results, a correlation between the flexural and the shear bond strengths has been determined and is presented in this paper.

Detecting anomalous events at railway level crossings

Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

Crowd monitoring using computer vision

Novel computer vision techniques have been developed for automatic monitoring of crowed environments such as airports, railway stations and shopping malls. Using video feeds from multiple cameras, the techniques enable crowd counting, crowd flow monitoring, queue monitoring and abnormal event detection. The outcome of the research is useful for surveillance applications and for obtaining operational metrics to improve business efficiency.

An evaluation of different features and learning models for anomalous event detection

The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Summarisation of short-term and long-term videos using texture and colour

We present a novel approach to video summarisation that makes use of a Bag-of-visual-Textures (BoT) approach. Two systems are proposed, one based solely on the BoT approach and another which exploits both colour information and BoT features. On 50 short-term videos from the Open Video Project we show that our BoT and fusion systems both achieve state-of-the-art performance, obtaining an average F-measure of 0.83 and 0.86 respectively, a relative improvement of 9% and 13% when compared to the previous state-of-the-art. When applied to a new underwater surveillance dataset containing 33 long-term videos, the proposed system reduces the amount of footage by a factor of 27, with only minor degradation in the information content. This order of magnitude reduction in video data represents significant savings in terms of time and potential labour cost when manually reviewing such footage.

The effects of low degree alteration on Sm-Nd and U-Pb isotope systematics in Eoarchean basalts from the Doolena Gap and Warralong Greenstone belts, Pilbara Craton, Western Australia

This research led to the discovery of one of the best preserved remnants of the Earth's surficial environment 3.47 billion years ago. These ancient volcanic and sedimentary rocks contain original minerals and textures that are rare in rocks of this age. The research concentrated on chemical analysis of volcanic rocks to differentiate secondary alteration from the primary magmatic signature. This study contributes to our understanding of melting processes and geochemical reservoirs in the early Earth, which is vital for forward modelling of Earth's geodynamic evolution.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

Fred’s Flow (Canada) and Murphy Well (Australia) : thick komatiitic lava flows with contrasting compositions, emplacement mechanisms and water contents

Two Archaean komatiitic flows, Fred’s Flow in Canada and the Murphy Well Flow in Australia, have similar thicknesses (120 and 160 m) but very different compositions and internal structures. Their contrasting differentiation profiles are keys to determine the cooling and crystallization mechanisms that operated during the eruption of Archaean ultramafic lavas. Fred’s Flow is the type example of a thick komatiitic basalt flow. It is strongly differentiated and consists of a succession of layers with contrasting textures and compositions. The layering is readily explained by the accumulation of olivine and pyroxene in a lower cumulate layer and by evolution of the liquid composition during downward growth of spinifex-textured rocks within the upper crust. The magmas that erupted to form Fred’s Flow had variable compositions, ranging from 12 to 20 wt% MgO, and phenocryst contents from 0 to 20 vol%. The flow was emplaced by two pulses. A first ~20-m-thick pulse was followed by another more voluminous but less magnesian pulse that inflated the flow to its present 120 m thickness. Following the second pulse, the flow crystallized in a closed system and differentiated into cumulates containing 30–38 wt% MgO and a residual gabbroic layer with only 6 wt% MgO. The Murphy Well Flow, in contrast, has a remarkably uniform composition throughout. It comprises a 20-m-thick upper layer of fine-grained dendritic olivine and 2–5 vol% amygdales, a 110–120 m intermediate layer of olivine porphyry and a 20–30 m basal layer of olivine orthocumulate. Throughout the flow, MgO contents vary little, from only 30 to 33 wt%, except for the slightly more magnesian basal layer (38–40 wt%). The uniform composition of the flow and dendritic olivine habits in the upper 20 m point to rapid cooling of a highly magnesian liquid with a composition like that of the bulk of the flow. Under equilibrium conditions, this liquid should have crystallized olivine with the composition Fo94.9, but the most magnesian composition measured by electron microprobe in samples from the flow is Fo92.9. To explain these features, we propose that the parental liquid contained around 32 wt% MgO and 3 wt% H2O. This liquid degassed during the eruption, creating a supercooled liquid that solidified quickly and crystallized olivine with non-equilibrium textures and compositions.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.

A new period of volcanogenic massive sulfide formation in the Yilgarn: A volcanological study of the ca 2.76 Ga Hollandaire VMS deposit, Yilgarn Craton, Western Australia

The Archean Hollandaire volcanogenic massive sulfide deposit is a felsic–siliciclastic VMS deposit located in the Murchison Domain of the Youanmi Terrane, Yilgarn Craton, Western Australia. It is hosted in a succession of turbidites, mudstones and coherent rhyodacite sills and has been metamorphosed to upper greenschist/lower amphibolite facies and includes a pervasive S1 deformational fabric. The coherent rhyodacitic sills are interpreted as syndepositional based on geochemical similarities with well-known VMS-associated felsic rocks and similar foliations to the metasediments. We offer several explanations for the absence of textural evidence (e.g. breccias) for syn-depositional origins: 1) the subaqueous sediments were dehydrated by long-lived magmatism such that no pore-water remained to drive quench fragmentation; 2) pore-space occlusion by burial and/or, 3) alteration overprinting and obscuring of primary breccias at contact margins. Mineralisation occurs by sub-seafloor replacement of original host rocks in two ore bodies, Hollandaire Main (~125 x >500 m and ~8 m thick) and Hollandaire West (~100 x 470 m and ~5 m thick), and occurs in three main textural styles, massive sulfides, which are exclusively hosted in turbidites and mudstones, and stringer and disseminated sulfides, which are also hosted in coherent rhyodacite. Most sulfides have textures consistent with remobilisation and recrystallisation. Hydrothermal metamorphism has altered the hangingwall and footwall to similar degrees, with significant gains in Mg, Mn and K and losses in Na, Ca and Sr. Garnet and staurolite porphyryoblasts also exhibit a footprint around mineralisation, extending up to 30 m both above and below the ore zone. High precision thermal ionisation mass spectrometry of zircons extracted from the coherent rhyodacite yield an age of 2759.5 ± 0.9 Ma, which along with geochemical comparisons, places the succession within the 2760–2735 Ma Greensleeves Formation of the Polelle Group of the Murchison Supergroup. Geochemical and geochronological evidence link the coherent rhyodacite sills to the Peter Well Granodiorite pluton ~2 km to the W, which acted as the heat engine driving hydrothermal circulation during VMS mineralisation. This study highlights the importance of both: detailed physical volcanological studies from which an accurate assessment of timing relationships, particularly the possibility of intrusions dismembering ore horizons, can be made; and identifying synvolcanic plutons and other similar suites, for VMS exploration targets in the Youanmi Terrane and worldwide.