OPUS

Schlimm, Katharina

Loades, Maria

Hards, Emily

Reynolds, Shirley

Parkinson, Monika

Midgley, Nicholas

University of Bath Research Portal

English

It’s always difficult when it’s family… whereas when you're talking to a therapist…’:Parents’ views of cognitive-behaviour therapy for depressed adolescents

Finn, Thomas

Stauffer, Alexandre

Non-equilibrium multi-scale analysis and coexistence in competing first passage percolation

Kivimaki, Timo

        Citation for published version:Kivimaki, T 2017, 'What South Korea’s election might mean for the long peace in East Asia?', The Conversation.<https://theconversation.com/what-south-koreas-election-might-mean-for-the-long-peace-in-east-asia-76845>Publication date:2017Link to publicationPublisher RightsCC BYUniversity of BathAlternative formatsIf you require this document in an alternative format, please contact:openaccess@bath.ac.ukGeneral rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 16. Nov. 2022 What South Korea’s election might mean for the long peace in East Asia May 9, 2017 2.27pm BST  After an election triggered by its last president’s impeachment, South Korea has a new leader, the Democratic Party’s Moon Jae-in. After the scandal that brought down his predecessor, he campaigned largely against corruption and on economic issues – but he was also forced to explain how he would handle his country’s northern neighbour.  During the last weeks of the election campaign, North Korea ramped up its missile tests and even hinted at an upcoming nuclear test. Experts and military officials said that the recent tests indicated that the country’s missile capabilities are advancing fast, and that Pyongyang could soon be able to fit a nuclear warhead onto an intercontinental ballistic missile.  As a result, some are concerned that a devastating war on the Korean peninsula might be in the offing. Should such a conflict erupt, it could turn out to be more intensive than any war the region has seen, even though the US and South Korea can reportedly intercept at least some North Korean missiles with their newly deployed Terminal High Altitude Area Defence (THAAD) system.  And yet, for almost four decades, East Asia has been more peaceful than Europe, the Americas, or any other continent, at least if peacefulness is measured by the number of conflict fatalities per head of population. So why is this the case – and might recent events on the Korean Peninsula put an end to this remarkably stable era?  One recent study found that one of the main reasons East Asia remains overwhelmingly peaceful is that almost all its states believe their number one job is to foster economic development at home. Most of them have duly pursued growth and development with something bordering on obsession. This naturally makes them reluctant to fight wars, which would by definition disrupt the economic interdependence that has helped make them so wealthy so fast.  There is clear evidence to back up this hypothesis: after World War II, those East Asian countries where the regime did not consider development a top priority saw on average more than 300 times as many conflict fatalities per million people as countries that put development first. After the 1970s, most countries became “developmentalist”, and North Korea is now a glaring exception. Easing the tension  Broadly speaking, the rest of East Asia now operates under a norm of military non-interference in the internal affairs of other countries. This is a stark contrast with the practice before the end of the Vietnam War, when wars in Korea, Laos, Cambodia, the Philippines, China, and elsewhere saw other countries offer ideologically driven support to both governments and their opponents.  The effect of this support is evident in the data. After World War II, two-thirds of East Asia’s conflict fatalities were caused by conflicts that started out as civil wars but were then internationalised when outside powers interfered – and in these wars, the internationalisation intensified killings by a factor of 20.  As the years went by, the norm changed. Since the late 1970s, East Asian powers have supported each other against insurgencies (such as the Philippines’ Mindanao conflict) but haven’t lent military support to the opponents of fellow governments. Some of this can be chalked up to the establishment of the Association of South-East Asian Nations, which provides a vital forum for resolving disputes. Also crucial was China’s metamorphosis into a developmentalist country that respected others’ sovereignty, another transition that began in the late 1970s. Testing the THAAD missile system, which is now deployed on the Korean Peninsula. EPA/Missile Defence Agency Handout  But today, North Korea’s human rights violations and nuclear weapons programme are putting the norm of non-interference under severe strain, as is the US’s increasingly interventionist stance. The disastrous conflicts in Afghanistan, Iraq, Libya, and Syria have taught authoritarian regimes that “sovereignty” is no longer respected as an absolute concept. North Korea’s leaders have duly invoked the threat of external intervention to justify harsh domestic policies. The threat from “imperial powers” is a handy pretext for cracking down on internal subversion and disobedience.  Clearly, the rest of the world’s approach to the north in recent years has done little to undermine this propagandist premise. And this is where Moon might make a difference.  For one, he has clearly signalled that he intends to pivot away from vague plans for regime change in North Korea, towards strategies for security and peace that don’t necessarily involve deposing the Kim regime. Instead of punishing and isolating North Korea, Moon would like to lull it into the same development-fixated mindset that has gripped the rest of East Asia for the last several decades.  Moon doesn’t believe that outside powers can or should force North Korea to democratise. Instead, he believes in dialogue, and the slow development of north-south relations. That could be a good fit with the businessman-like approach preferred by Donald Trump, who now says he’s open to to direct dialogue with the Kim government – that is, provided this recent turn in Trump’s rhetoric overrides the more hawkish elements in his administration.  If a catastrophic war on the Korean peninsula is to be averted, Moon will have to use all the political and diplomatic tools at his disposal. Fortunately, East Asia’s decades of successful, peaceful economic integration and developmentalism offer him a clear set of norms by which to abide. For all that the situation seems to be getting closer to outright conflict, a less interventionist South Korean approach to the north may be in the offing. 

What South Korea’s election might mean for the long peace in East Asia?

Schäfer, Pascal M

Fuchs, Martin

Ohligschläger, Andreas

Rittinghaus, Ruth

McKeown, Paul

Akin, Enver

Schmidt, Maximilian

Hoffmann, Alexander

Liauw, Marcel A.

Jones, Matthew

Herres-Pawlis, Sonja

Highly Active N,O Zinc Guanidine Catalysts for the Ring-Opening Polymerization of Lactide

Packham, Jonathan C

Abraham, Sonya

Kirkham, Bruce

Helliwell, Philip

Siebert, Stefan

Korendowych, Ellie

Fitzgerald, Oliver

Parkinson, Andrew

Brookes, Mel

Coates, Laura

McHugh, Neil

A New Era for Collaboration?Strapline: Clinical, Academic and Patient Consortiums Jonathan C Packham 1, Sonya Abraham2, Bruce Kirkham3, Philip Helliwell4, Stefan Siebert5, Ellie Korendowych 6, Oliver Fitzgerald 7, Andrew Parkinson 8, Mel Brookes 9, Laura Coates 4 and Neil McHugh10Institute of Applied Clinical Science, Keele University, Keele, UKNIHR/Wellcome clinical research facility, Imperial College, London, UKDepartment of Rheumatology, Guy's & St Thomas' NHS Foundation Trust, London, UKLeeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UKInstitute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UKDepartment of Rheumatology, Royal National Hospital for Rheumatic Diseases, Bath, UK St Vincent's University Hospital and Conway Institute for Biomolecular Research, University College Dublin, Dublin, Ireland Patient partner, Leeds, UK Psazz, psoriatic arthritis support group, Bath, UK Department of Pharmacy and Pharmacology, University of Bath, Bath, UKCorrespondence to:  Jonathan Packham, Institute of Applied Clinical Science, Keele University, Keele, ST5 5BG, UK. E-mail: Jon.Packham@ssotp.nhs.uk.For clinicians and clinical academics with an interest in less common diseases, there is an on-going challenge of how to promote best practice and encourage the development of research studies to inform evidence based clinical practice. By combining expertise and resources and providing a central focus of activity, clinicians specialising in treating and researching these diseases can beneficially influence disease awareness across patients, healthcare professionals and politicians. Working as a collaborative network should ensure the quality and clinical utility of new research ideas and improve research participant recruitment, enhancing the likelihood of developing successful research studies with funders and pharmaceutical companies.  A new collaboration of academically interested clinicians and patients across the UK (British Psoriatic Arthritis Consortium Brit-PACT) acting as a focus for disease education and a platform for epidemiological, biomarker and pharmaceutical studies may provide a blueprint for success in other disease areas. Early successes include the prioritisation of unmet needs in psoriatic arthritis (PsA) research, care and management and Brit-PACT input into NHS choices patient information on PsA.The consortium acts as a national hub to liaise with world-wide psoriatic arthritis research groups and with other linked disease-specific groups such as BRITSpA (a sister UK clinical academic research group for axial spondyloarthropathy) and dermatology stakeholders. The steering group includes many of the active clinical researchers across the UK, patient partners and an international advisor from Ireland. Brit-PACT’s strength lies in the combination of patient and professional input, with a strong focus on a single disease and associated comorbidities. This allows the group an immediate advantage in the development, submission and promotion of research studies which are relevant to patients and clinicians alike. Linking with similar existing groups (or helping develop these in countries without an established collaborative infrastructure), would promote independent group/country initiatives, and enhance collaborative work at a European level or wider. Linking groups may be a valuable method of developing internationally collaborative research designed to answer important clinical, epidemiological and pathogenesis related questions and enhance clinical care.   It is perhaps surprising that for many chronic inflammatory diseases there is a real paucity of research to support widely accepted clinical practices. These areas are often highlighted by experts in the condition whilst clinical decision aids, such as EULAR, GRAPPA, BSR or NICE guidelines, are being developed.  However, often there is no established infrastructure to develop or fund research into these highlighted areas of unmet need, to improve the potential for truly evidence based practice. Collaborative groups of clinical academics and patients working together, have the potential to refine and prioritise research questions which make a real difference to patient care in the future. The strategy of patients playing an equal part within the Consortium ensures patient and public involvement in all activities, at each stage and at all levels.  A variety of patient and professional organisations along with charities work hard to raise awareness of rheumatological conditions for patients, health professionals and decision makers. However, these bodies often have to promote across the wide spectrum of musculoskeletal diseases. This understandably results in the more commonly occurring musculoskeletal diseases, such as back pain, osteoarthritis and rheumatoid arthritis receiving the focus of attention. Diseases which occur less frequently, such as psoriatic arthritis, axial spondyloarthritis, SLE and scleroderma may be championed enthusiastically by disease specific organisations (often patient groups). However, these groups often come under umbrella organisations, such as the Arthritis and Musculoskeletal Alliance (ARMA) in the UK.  ARMA has been particularly successful in raising the profile of musculoskeletal diseases to politicians and decision makers, but by coming together to improve visibility and be representative of a larger population, there is a risk that disease specific focus may be lost.     Although national grant awarding charities often have dedicated clinical studies groups providing strategic direction for the development of clinical research ideas, they are often limited by the relatively tight remits.  For example, some groups focus on interventional studies to the exclusion of biomarker or cohort collection, and most have a country limited focus. Groups such as Brit-PACT, with a strong partnership between patients and research interested health professionals can be an invaluable resource to ensure study design and grant applications are of high quality with appropriate focus on areas important to both patients and clinicians. This potentially improves the likelihood of not only successful study funding and completion, but also implementation of research into clinical practice for the benefit of patients.Both charities and national/international funding bodies experience difficulties in their relationships and potential partnerships with the pharmaceutical industry.  Research-related relationships between the pharmaceutical industry and clinical academics are already considerable and have had an essential role in translating the discoveries of basic biological research into new therapies. However, there is a dissonance in understanding the need for such collaborations and their endorsement. We believe that the wider rheumatology community would support academics collaborating with pharmaceutical companies, if this resulted in research which benefits patients. However, without maintaining academic independence, researchers run the risk of being accused of bias. Academics and industry need to find practical and durable solutions for the best and most appropriate ways to work together and be productive whilst maintaining both real and perceived independence. A possible answer to this problem is for nationally collaborative groups, rather than individual academics, to work with industry to develop mutually beneficial studies with a wider remit than simply providing proof of therapeutic response, and with more of a focus on patient benefit.Patient and health professional disease education can also be championed by collaborative groups like Brit-PACT. They can act as a resource of clinical expertise for patient groups providing patient information and education. Their independent status provides the opportunity to kite mark the quality of educational activities of others (such as patient organisations and pharmaceutical companies).Brit-PACT has been created to bring together patients and professionals with an interest in psoriatic arthritis. We believe this is a good exemplar of how clinicians working in rheumatology can both promote disease awareness and also lead/inform clinically relevant research across different countries and clinical areas. AcknowledgmentsBrit PACT has received infrastructure and educational meeting financial support from Pfizer, Abbvie, Celgene, Janssen, Novartis and UCB. Funding: No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this manuscript. Disclosure statement: J.P. has received honoraria from Abbvie for educational meetings. N.J.M. has received honoraria and or research grants from Abbvie, Celgene and Pfizer. P.H. has consulted for AbbVie, Amgen, Celgene, Janssen, MSD, and UCB. E.K. has received Consultancy fees for Abbvie, Novartis, Janssen, UCB and Pfizer and their department has received research funding from Abbvie and Pfizer. S.M.A. has received educational and research bursaries from AbbVie, Celgene, MSD, Novartis, Pfizer and UCB pharma. O.F. has received honoraria and grants/research support from AbbVie, Novartis, Jansen, BMS, Celgene, UCB and Pfizer. B.K. has received research support from Abbvie, Eli Lilly & Company, Novartis, Roche Pharmaceuticals and honoraria from Eli Lilly & Company, Janssen, Novartis and Pfizer. L.C. has received research funding and/or honoraria from AbbVie, BMS, Celgene, Janssen, Lilly, MSD, Pfizer, Novartis, Sun Pharma and UCB. S.S. has received honoraria for advice or being a member of a speaker's bureau from Abbvie, Janssen, Pfizer, Novartis, Boehringer Ingelheim and UCB, and has received research grants from Janssen, UCB, Pfizer, Celgene and Boehringer Ingelheim. All other authors have declared no conflicts of interest.References1. D.Malakoff. (2013) The Many Ways of Making Academic Research Pay Off. Science 339:750-7532. M.Angell. (2000) Is Academic Medicine for Sale?. N Engl J Med 343:508-5103. A.S. Relman (2001) Separating Continuing Medical Education from Pharmaceutical Marketing. JAMA 285:2009-2012

A new era for collaboration?

Jadon, Deepak R

Nightingale, Alison L

McHugh, Neil J

Lindsay, Mark A

Korendowych, Eleanor

Sengupta, Raj

Serum Soluble Bone Turnover Biomarkers in Psoriatic Arthritis and Psoriatic Spondyloarthropathy

Li, Shuangqi

Zhao, Pengfei

Gu, Chenghong

Huo, Da

Zeng, Vincent

Pei, Xiaoze

Cheng, Shuang

Li, Jianwei

Online battery-protective vehicle to grid behavior management

Isupova, Olga

Kuzin, Danil

Mihaylova, Lyudmila S.

        Citation for published version:Isupova, O, Kuzin, D & Mihaylova, LS 2016 'Anomaly detection in video with Bayesian nonparametrics'.Publication date:2016Link to publicationUniversity of BathAlternative formatsIf you require this document in an alternative format, please contact:openaccess@bath.ac.ukGeneral rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 12. Jan. 2023Anomaly Detection in Videowith Bayesian NonparametricsOlga Isupova O.ISUPOVA@SHEFFIELD.AC.UKDanil Kuzin DKUZIN1@SHEFFIELD.AC.UKLyudmila Mihaylova L.S.MIHAYLOVA@SHEFFIELD.AC.UKThe University of Sheffield,Western Bank, Sheffield, S10 2TN, UKAbstractA novel dynamic Bayesian nonparametric topicmodel for anomaly detection in video is proposedin this paper. Batch and online Gibbs samplersare developed for inference. The paper intro-duces a new abnormality measure for decisionmaking. The proposed method is evaluated onboth synthetic and real data. The comparisonwith a non-dynamic model shows the superiorityof the proposed dynamic one in terms of the clas-sification performance for anomaly detection.1. IntroductionTopic modeling (Hofmann, 1999; Blei et al., 2003) is apromising approach for anomaly detection in video (Jeonget al., 2014; Varadarajan & Odobez, 2009; Mehran et al.,2009). This is an unsupervised method which means thatthere is no need to predict all kinds of abnormalities in ad-vance and collect a labelled dataset for it. Topic model-ing also provides additional information about typical mo-tions and behaviours rather than just warns about abnormalevents.In the text mining application a topic model represents un-labelled documents as mixtures of topics where unknowntopics are distributions over observed words. In conven-tional topic modeling documents are assumed to be inde-pendent. Although in some cases this assumption is notvalid and different dynamic models are proposed in theliterature (Blei & Lafferty, 2006; Ahmed & Xing, 2010;Hospedales et al., 2012; Kuettel et al., 2010; Pruteanu-Malinici et al., 2010; Srebro & Roweis, 2005; Zhang et al.,2010).Presented at ICML2016 Anomaly Detection Workshop, New York,NY, USA, 2016. Copyright 2016 by the author(s).In the video processing application short video clips areoften treated as documents, local motion patterns are rep-resented by topics. All motions in the real life last for sometime hence topic mixtures in the successive documents areexpected to be similar if the clips are sufficiently short.We propose a dynamic nonparametric topic model foranomaly detection. Successive documents are encouragedto have similar topic mixtures.Anomaly detection is an urgent task; the decision shouldbe made as soon as possible. Batch and online Gibbs sam-pler is proposed in this paper. The online inference algo-rithm allows to estimate parameters for the current docu-ment with no need to rerun it on the previous ones. Anabnormality measure for decision making is also proposedin the paper.The paper is organised as follows. Section 2 defines vi-sual words and documents while section 3 describes theproposed model. The inference and the whole frameworkare introduced in sections 4 and 5 respectively. Evaluationof the method using synthetic and real data is presented insection 6 followed by the conclusions in section 7.2. Visual FeaturesThe definitions of visual words and visual documents areessential for topic modeling application to video process-ing. A quantised direction (Figure 1) of an average opticalflow vector (Horn & Schunck, 1981) overN×N pixels andits location form a visual word. Non-overlapping clips ofthe whole video sequence are treated as visual documents.3. Proposed ModelLet x1:J = {xj}j=1:J denote a sequence of docu-ments. A document xj consists of Nj words xji: xj ={xji}i=1:Nj . Documents are assumed to be mixtures oftopics {φk}k=1:∞, which are the latent distribution overarXiv:1606.08455v1  [stat.ML]  27 Jun 2016Anomaly Detection in Video with Bayesian NonparametricsFigure 1. Optical flow direction quantisation. The four main di-rections are extracted — up, right, down and left, highlighted bythe colour on the figure.words. The number of possible topics is expected to go toinfinity for an infinite amount of data.3.1. Hierarchical Dirichlet Process Topic ModelA hierarchical Dirichlet process (HDP) (Teh et al., 2006)can represent mixture models with a potentially infinitenumber of mixture components.A HDP can be represented in different ways, Chineserestaurant franchise (CRF) is reviewed here. Documentsare considered as “restaurants” and words are consideredas “customers” in this metaphor. The words in the docu-ments form groups around “tables” and eat the same “dish”,which corresponds to a topic, on one table. The set of thetopics is shared among all the documents, that creates a“franchise” of the restaurants.Denote a table assignment of the token i in the document jby tji, a topic assignment of the table t in the document jby kjt. The following counts are used: njt for the numberof words assigned to the table t in the document j and mjkfor the number of tables serving the topic k in the documentj. Let dots in subscripts denote marginalisation over thecorresponding dimension.The generative process is the following. Each token i inthe document j chooses one of the occupied tables with aprobability proportional to a number njt of words alreadyassigned to a table, or the token starts a new table with aprobability proportional to a parameter α:p(tji = t|tj1, . . . , tji−1, α) =njti− 1 + α, if t = 1 : mj·;αi− 1 + α, if t = tnew.(1)If a new table is started the topic should be assigned to it.It can be one of the used topics with a probability propor-tional to a numberm·k of tables having this topic among allthe documents, or it can be a new topic with a probabilityproportional to a parameter γ:p(kjtnew = k|k11, . . . , kjt−1, γ) =m·km·· + γ, if k = 1 : K;γm·· + γ, if k = knew,(2)where K is a number of topics used so far. In the case of anew topic it is sampled from the base measure H .The word xji for the topic i in the document j assigned tothe table tji is sampled from the topic kjtji served on thistable:xjt ∼ Mult(φkjtji ). (3)3.2. Dynamic Hierarchical Dirichlet Process TopicModelExchangeability of documents and words is an essential as-sumption in the HDP, which means that the joint probabil-ity of the data is independent of the order of the documentsand words. Although in video processing this assumptionis not reasonable. Motions last for some time and it is ex-pected that the topic mixture of the current document issimilar to the topic mixture in the previous one. However,the words inside documents are still exchangeable.The dynamic extension of the HDP topic model is proposedin this paper to take into account this intuition. The prob-ability of the topic k being assigned to one of the tables inthe document j explicitly depends on the usage of this topicin the current and previous documents mjk +mj−1k. Thetopic distribution of the current document is hence encour-aged to be similar to the topic distribution of the previousone.The proposed model assumes the following generativeprocess. A table assignment for a token remains un-changed (1). A topic for a new table in the document jis assigned to one of the used topics k with a probabilityproportional to the sum of the number of tables serving thistopic in the current and previous documents mjk +mj−1kand the weighted number of tables among all the docu-ments that have this topic δ m·k, where δ is a parameter ofthe model, or it is assigned to a new topic with a probabilityproportional to the parameter γ:p(kjt = k|k11, . . . , kjt−1, γ) =mjk +mj−1k + δm·kmj· +mj−1· + δm·· + γ, if k = 1 : K;γmj· +mj−1· + δm·· + γ, it k = knew.(4)The word xji is sampled as in the HDP from the corre-sponding topic as defined in (3).Anomaly Detection in Video with Bayesian NonparametricsTable 1. AUC results.DATA SET DYNAMIC HDP HDP “TRUE” MODELSYNTHETIC 0.7118 0.4751 0.7280QMUL 0.7100 0.4644 —4. InferenceConventional inference algorithms are batch algorithms,i.e. they process the whole dataset, which is computation-ally intractable for large or stream datasets. Online algo-rithms work sequentially, one data point at a time. We pro-pose a combination of offline and online inference for ourmodel.We use Gibbs sampling (Geman & Geman, 1984). Thehidden variables t = {tji}j=1:J,i=1:Nj and k ={kjt}j=1:J,t=1:mj· are sampled from their conditional dis-tributions.The batch Gibbs sampler is run for the training set of thedocuments. After this training stage the global estimatesof the topics φk and the counts m·k for all k are storedand used for the online inference of the testing documents.For each testing document the online Gibbs sampler is runto sample table assignments and topic assignments for thisdocument only. The online Gibbs sampler updates the localcounts mjk. After the Gibbs sampler converges, the globalvariables φk and m·k are updated with the information ob-tained by the new document.5. Anomaly DetectionAnomaly detection can be done within the probabilisticframework using topic modeling. In this framework thedata point is assumed to be abnormal if it has a low valueof likelihood, i.e. the learnt model cannot explain the cur-rent observation because something atypical is happening.We use the predictive likelihood estimated as a harmonicmean (Griffiths & Steyvers, 2004) and normalised by thelength Nj of the document for anomaly detection.6. ExperimentsThe proposed method1 is applied for anomaly detection onsynthetic and real data. We compare it with the methodbased on the HDP topic model (for the batch Gibbs sam-pler of the HDP topic model the implementation by ChongWang is used2). For the quantitative comparison the area(AUC) under the receiver operating characteristic (ROC)1https://github.com/OlgaIsupova/dynamic-hdp2https://github.com/Blei-Lab/hdpFigure 2. Graphical representation of the topics in the syntheticdataset. There are 25 words, organised into a 5× 5 matrix, wherea word corresponds to a cell in this matrix. The topics are repre-sented as the coloured matrices, where the colour of the cell indi-cates the probability of the corresponding word in a given topic,the lighter the colour the higher the probability value is.False positive rate0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Truepositiverate00.10.20.30.40.50.60.70.80.91ROC-curves on synthetic dataDynamic HDPHDP”True” modelFigure 3. The ROC-curves for the synthetic data.curve (Murphy, 2012) for abnormality classification accu-racy is used.6.1. Synthetic DataThe “bar” data introduced in (Griffiths & Steyvers, 2004) isused. The vocabulary consists of V = 25 words, organisedinto a 5× 5 matrix. The topics {φk}10k=1 form vertical andhorizontal bars in the matrix (Figure 2).Within the testing dataset we generate some “abnormal”documents where topics are chosen uniformly from the setof all the topics except those used in the previous docu-ments. The data generated in such a way contradicts themain model assumption that the topic mixtures of the suc-cessive documents should be similar.Figure 3 presents the obtained ROC-curves for anomaly de-tection. For the reference we also show the ROC-curve forthe “true” model, i.e. the model with the true topics φk andAnomaly Detection in Video with Bayesian Nonparametrics(a) (b) (c) (d)Figure 4. QMUL-junction dataset snapshots. (a) is an example of a normal motion, (b) is an example of jay-walking abnormality, (c) isan example of a car moving on the wrong lane in the opposite to normal direction, (d) is an example an emergency service car disruptinga normal traffic flow.the true table and topic assignments t and k. This modelrepresents the one that can perfectly restore all the latentvariables. The corresponding AUC values are in Table 1.The proposed dynamic HDP shows the anomaly detectionperformance competitive to the “true” model.6.2. Real DataWe also test the algorithms on the QMUL-junction realvideo data (Hospedales et al., 2012) captured a busy roadjunction (Figure 4(a)). 5 out of 45 minutes of the video se-quence is used as a training dataset for offline Gibbs sam-pler.For the ground truth reference the data is labelled as nor-mal and abnormal, where abnormal event examples arejay-walking (Figure 4(b)), driving wrong direction (Fig-ure 4(c)), disruption in traffic flow (Figure 4(d)).Figure 5 presents the ROC-curves while Table 1 containsthe corresponding AUC values. The experiment confirmsthat the dynamics consideration in a topic model improvesthe anomaly detection performance.7. ConclusionsA novel Bayesian nonparametric dynamic topic model isproposed in this paper. Batch and online inference algo-rithms are designed. Anomaly detection in video is consid-ered as an application of the model for which we proposean abnormality measure. The experimental results both onsynthetic and real data show that the proposed dynamictopic model improves the anomaly detection performancein comparison to the non-dynamic model.AcknowledgmentsThis work is accepted to the 19th International Confer-ence on Information Fusion 2016. Olga Isupova and Lyud-mila Mihaylova acknowledge the support from the EC Sev-enth Framework Programme [FP7 2013-2017] TRAcking0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1False positive rate00.10.20.30.40.50.60.70.80.91TruepositiverateROC-curves on QMUL dataDynamic HDPHDPFigure 5. The ROC-curves for the QMUL data.in compleX sensor systems (TRAX) Grant agreement no.:607400. Lyudmila Mihaylova acknowledges also the sup-port from the UK Engineering and Physical Sciences Re-search Council (EPSRC) via the Bayesian Tracking andReasoning over Time (BTaRoT) grant EP/K021516/1.ReferencesAhmed, Amr and Xing, Eric. Timeline: A dynamic hierar-chical Dirichlet process model for recovering birth/deathand evolution of topics in text stream. In Proceedings ofthe Twenty-Sixth Conference Annual Conference on Un-certainty in Artificial Intelligence (UAI-10), pp. 20–29,Corvallis, Oregon, 2010. AUAI Press.Blei, David M. and Lafferty, John D. Dynamic topic mod-els. In Proceedings of the 23rd International Conferenceon Machine Learning, ICML ’06, pp. 113–120, NewYork, NY, USA, 2006. ACM.Blei, David M., Ng, Andrew Y., and Jordan, Michael I. La-Anomaly Detection in Video with Bayesian Nonparametricstent Dirichlet allocation. Journal of Machine LearningResearch, 3:993–1022, March 2003.Geman, Stuart and Geman, Donald. 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