HMM-Based Abnormal Behaviour Detection Using Heterogeneous Sensor Network

  title={HMM-Based Abnormal Behaviour Detection Using Heterogeneous Sensor Network},
  author={Hadi Aliakbarpour and Kamrad Khoshhal and Jo{\~a}o Quintas and Kamel Mekhnacha and Julien Ros and Maria Andersson and J. Dias},
This paper proposes a HMM-based approach for detecting abnormal situations in some simulated ATM (Automated Teller Machine) scenarios, by using a network of heterogeneous sensors. The applied sensor network comprises of cameras and microphone arrays. The idea is to use such a sensor network in order to detect the normality or abnormality of the scenes in terms of whether a robbery is happening or not. The normal or abnormal event detection is performed in two stages. Firstly, a set of low-level… 

Using concurrent Hidden Markov Models to analyse human behaviours in a smart home environment

The proposed approach successfully implements concurrent Hidden Markov Models that identify the occurring situation and corresponds to the highlevel part from a framework to obtain high-level classification of human behaviour analysis.

A Self-adaptive Multi-Agent System for Abnormal Behavior Detection in Maritime Surveillance

This paper presents a MAS dedicated to abnormal behaviors detection and alerts triggering in the maritime surveillance area. This MAS uses anomalies issued from an experienced Rule Engine

Recurrent Transformation of Prior Knowledge Based Model for Human Motion Recognition

This study starts from a deep analysis on natural physical properties and temporal recurrent transformation possibilities of human motions and then proposes a useful Recurrent Transformation Prior Knowledge-based Decision Tree (RT-PKDT) model for recognition of specific human motions.

Detecting Abnormal Patterns of Daily Activities for the Elderly Living Alone

An automated method that is able to detect abnormal patterns of the elderly’s entering and exiting behaviors collected from simple sensors equipped in home-based setting is developed.

Analysis of fault of insulation aging of oiled paper of a large‐scale power transformer and the prediction of its service life

  • Peng Xie
  • Physics
    IEEJ Transactions on Electrical and Electronic Engineering
  • 2019
Insulation aging of oiled paper is a common malfunction of transformers. It is of great value to recognize the insulation aging status of oiled paper and predict the service life of transformers

Auto-Adaptive Interactive Systems for Active and Assisted Living Applications

The hypothesis is that, HMI can overcome limitations of current interaction functionalities by integrating contextual information to improve algorithms accuracy when performing under very different conditions and to adapt interfaces and interaction patterns according user intentions and emotional states.

The Role of Context Information in Human-Robot Interaction

The role of context information is discussed, which is claimed to be a key factor to improve interactive features in robots and systems and a conceptual adaptation to common existing architectures is proposed in order to take into account with contextual information in human-robot interaction.

Self-adaptive multi-agent systems for aided decision-making : an application to maritime surveillance

L'activite maritime s'est fortement developpee ces dernieres annees et sert de support a de nombreuses activites illicites. Il est devenu necessaire que les organismes impliques dans la surveillance

Exploiting Inertial Planes for Multi-sensor 3D Data Registration

Tese de doutoramento em Engenharia Eletrotecnica e de Computadores, no ramo de especializacao em Automacao e Robotica, apresentada a Faculdade de Ciencias e Engenharia da Universidade de Coimbra



Probabilistic LMA-based classification of human behaviour understanding using Power Spectrum technique

A Bayesian network is presented to understand human action and behaviour based on 3D spatial data and using the LMA concept which is a known human movement descriptor to classify actions.

Crowd behavior analysis under cameras network fusion using probabilistic methods

The crowd analysis is achieved in camera networks information by using the optical flow, and the Hidden Markov models and Bayesian Networks are compared to understand the agents behavior in the scene.

Heterogeneous Sensor Database in Support of Human Behaviour Analysis in Unrestricted Environments: The Audio Part

The design and the implementation of the audio part of the PROMETHEUS database is discussed and statistical information about the audio content is offered and it is confirmed that a major portion of the database will be made publically available by the end of year 2010.

Towards HMM based human motion recognition using MEMS inertial sensors

A new method of human motion recognition based on MEMS inertial sensors data, which consists of three dimensional MEMS accelerometers, gyroscopes, a Bluetooth module and a MCU (Micro Controller Unit), which can record and transfer inertial data to a computer through serial port wirelessly is presented.

A Novel Framework for Data Registration and Data Fusion in Presence of Multi-modal Sensors

This article presents a novel framework to register and fuse hetero- geneous sensory data. Our approach is based on geometrically registration of sensory data onto a set of virtual parallel planes

Real time, online detection of abandoned objects in public areas

The method presented here addresses the online and real time aspects of such systems, utilizes logic to differentiate between abandoned objects and stationary people, and is robust to temporary occlusion of potential abandoned objects.

Homography based multiple camera detection and tracking of people in a dense crowd

  • R. EshelY. Moses
  • Computer Science
    2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
A method for simultaneously tracking all the people in a densely crowded scene using a set of cameras with overlapping fields of view that was successful in tracking up to 21 people walking in a small area, in spite of severe and persistent occlusions.

Nonparametric discriminant HMM and application to facial expression recognition

This paper introduces an effective nonparametric output probability estimation method to increase the discrimination ability at both hidden state level and class level and presents a general formula for the estimation of output probability, which provides a way to develop new HMMs.

A tutorial on hidden Markov models and selected applications in speech recognition

The fabric comprises a novel type of netting which will have particular utility in screening out mosquitoes and like insects and pests. The fabric is defined of voids having depth as well as width

Human silhouette volume reconstruction using a gravity-based virtual camera network

The article represents a method to perform the Shape From Silhouette (SFS) of human, based on gravity sensing, using a network of cameras to observe the scene and validate both feasibility and effectiveness of the proposed method.