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Multimodal Affective State Recognition in Serious Games applications

Multimodal Affective State Recognition in Serious Games Appl...

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IEEE International conference on Imaging Systems and Techniques (IST) / IEEE International School on Imaging

作者： Psaltis, Athanasios Kaza, Kyriaki Stefanidis, Kiriakos Thermos, Spyridon Apostolakis, Konstantinos C. Dimitropoulos, Kosmas Daras, Petros Ctr Res & Technol Hellas Inst Informat Technol Thessaloniki Greece

ISBN: (纸本)9781509018178

A challenging research issue, which has recently attracted a lot of attention, is the incorporation of emotion recognition technology in serious games applications, in order to improve the quality of interaction and enhance the gaming experience. To this end, in this paper, we present an emotion recognition methodology that utilizes information extracted from multimodal fusion analysis to identify the affective state of players during gameplay scenarios. More specifically, two mono-modal classifiers have been designed for extracting affective state information based on facial expression and body motion analysis. For the combination of different modalities a deep model is proposed that is able to make a decision about player's affective state, while also being robust in the absence of one information cue. In order to evaluate the performance of our methodology, a bimodal database was created using Microsoft's Kinect sensor, containing feature vectors extracted from users' facial expressions and body gestures. The proposed method achieved higher recognition rate in comparison with mono-modal, as well as early-fusion algorithms. Our methodology outperforms all other classifiers, achieving an overall recognition rate of 98.3%.

关键词： emotion recognition multimodal fusion serious games

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Software Defined Multi-Spectral Imaging for Arctic sensor Networks 22

Software Defined Multi-Spectral Imaging for Arctic Sensor Ne...

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22nd SPIE conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII

作者： Siewert, Sam Angoth, Vivek Krishnamurthy, Ramnarayan Mani, Karthikeyan Mock, Kenrick Singh, Surjith B. Srivistava, Saurav Wagner, Chris Claus, Ryan Vis, Matthew Demi Embry Riddle Aeronaut Univ Prescott 3700 Willow Creek Rd Prescott AZ 86301 USA Univ Colorado Campus Box 425 Boulder CO 80309 USA Arctic Domain Awareness Ctr 3211 Providence Dr Anchorage AK 99508 USA Univ Alaska Anchorage 3211 Providence Dr Anchorage AK 99508 USA

ISBN: (纸本)9781510600812

Availability of off-the-shelf infrared sensors combined with high definition visible cameras has made possible the construction of a Software Defined Multi-Spectral Imager (SDMSI) combining long-wave, near-infrared and visible imaging. The SDMSI requires a real-time embedded processor to fuse images and to create real-time depth maps for opportunistic uplink in sensor networks. Researchers at Embry Riddle Aeronautical University working with University of Alaska Anchorage at the Arctic Domain Awareness Center and the University of Colorado Boulder have built several versions of a low-cost drop-in-place SDMSI to test alternatives for power efficient image fusion. The SDMSI is intended for use in field applications including marine security, search and rescue operations and environmental surveys in the Arctic region. Based on Arctic marine sensor network mission goals, the team has designed the SDMSI to include features to rank images based on saliency and to provide on camera fusion and depth mapping. A major challenge has been the design of the camera computing system to operate within a 10 to 20 Watt power budget. This paper presents a power analysis of three options: 1) multi-core, 2) field programmable gate array with multi-core, and 3) graphics processing units with multi-core. For each test, power consumed for common fusion workloads has been measured at a range of frame rates and resolutions. Detailed analyses from our power efficiency comparison for workloads specific to stereo depth mapping and sensor fusion are summarized. Preliminary mission feasibility results from testing with off-the-shelf long-wave infrared and visible cameras in Alaska and Arizona are also summarized to demonstrate the value of the SDMSI for applications such as ice tracking, ocean color, soil moisture, animal and marine vessel detection and tracking. The goal is to select the most power efficient solution for the SDMSI for use on UAVs (Unoccupied Aerial Vehicles) and other drop-in-pl

关键词： software defined multi-spectral imager field programmable gate array general purpose graphics co-processor sensor fusion stereo vision long-wave infrared near-infrared Arctic saliency power efficient real-time

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Indoor SLAM for Micro Aerial Vehicles Using Visual and Laser sensor fusion 2nd

Indoor SLAM for Micro Aerial Vehicles Using Visual and Laser...

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2nd Iberian Robotics conference (ROBOT)

作者： Lopez, Elena Barea, Rafael Gomez, Alejandro Saltos, Alvaro Bergasa, Luis M. Molinos, Eduardo J. Nemra, Abdelkrim Alcala Univ Dept Elect Alcala De Henares Spain Ecole Mil Polytech Algiers Algeria

ISBN: (纸本)9783319271460;9783319271453

This paper represents research in progress in Simultaneous Localization and Mapping (SLAM) for Micro Aerial Vehicles (MAVs) in the context of rescue and/or recognition navigation tasks in indoor environments. In this kind of applications, the MAV must rely on its own onboard sensors to autonomously navigate in unknown, hostile and GPS denied environments, such as ruined or semidemolished buildings. This article aims to investigate a new SLAM technique that fuses laser and visual information, besides measurements from the inertial unit, to robustly obtain the 6DOF pose estimation of a MAV within a local map of the environment. Laser is used to obtain a local 2D map and a footprint estimation of the MAV position, while a monocular visual SLAM algorithm enlarges the pose estimation through an Extended Kalman Filter (EKF). The system consists of a commercial drone and a remote control unit to computationally afford the SLAM algorithms using a distributed node system based on ROS (Robot Operating System). Some experimental results show how sensor fusion improves the position estimation and the obtained map under different test conditions.

关键词： Micro Aerial Vehicles Indoor navigation sensor fusion Simultaneous Localization and Mapping Robot Operating System

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Hardware Acceleration of Maximum-Likelihood Angle Estimation for Automotive MIMO Radars

Hardware Acceleration of Maximum-Likelihood Angle Estimation...

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conference on Design and architectures for Signal and Image Processing (DASIP)

作者： Meinl, Frank Kunert, Martin Blume, Holger Robert Bosch GmbH Adv Engn Sensor Syst Leonberg Germany Leibniz Univ Hannover Inst Mikroelekt Syst Hannover Germany

ISBN: (纸本)9791092279153

Direction of arrival (DOA) estimation is an important array signal processing technique, used by various applications such as radar, sonar or wireless communication. Most of the known DOA algorithms suffer from a significant performance reduction and even fail completely under difficult conditions, like small antenna aperture size, correlated signals or a small number of snapshots. Maximum-Likelihood (ML) methods have been investigated thoroughly and are known to still work even in such difficult scenarios. Though, the major drawback of ML methods is their computational cost, especially in the case of large MIMO (multiple-input multiple-output) configurations. This work presents a novel hardware accelerator architecture, which is able to compute the exact ML estimation in the case of one or two targets. It is shown, that the computational demanding vector product can be implemented with the help of CORDIC units, which help to save a considerable amount of hardware resources. Furthermore, the result of the single target estimator can be reused to efficiently compute the estimates in the two-target case. Finally, the performance of the architecture is evaluated by a FPGA implementation which is able to process more than 20 000 detections from 16 channels with 256 steering vectors in real-time (25 Hz).

关键词： Automotive radar driver assistance direction of arrival maximum-likelihood estimation radar signal processing CORDIC hardware accelerator FPGA

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Road surface classification using automotive ultrasonic sensor 30

Road surface classification using automotive ultrasonic sens...

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30th Eurosensors conference

作者： Bystrov, Aleksandr Hoare, Edward Thuy-Yung Tran Clarke, Nigel Gashinova, Marina Cherniakov, Mikhail Univ Birmingham Birmingham B15 2TT W Midlands England Jaguar Land Rover Res Dept Coventry CV3 4LF W Midlands England

This work examines the method of road surface classification, based on the analysis of backscattered ultrasonic signals. The novelty of our research is the extraction of signal features for separate swathes of illuminated surface (segmentation) and the use of a wide range of statistical methods in real on-road and off-road driving conditions. The errors caused by the influence of environmental conditions and the vehicle movement were analysed, and ways to reduce them were suggested. The results demonstrate the feasibility of reliable surface classification using the proposed methodology. (C) 2016 The Authors. Published by Elsevier Ltd.

关键词： sonar applications remote sensing sensor fusion classification algorithms artificial neural networks

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Holonic Multi Agent System for Data fusion in Vehicle Classification 10th

Holonic Multi Agent System for Data Fusion in Vehicle Classi...

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10th KES conference on Agent and Multi-Agent Systems - Technologies and applications (KES-AMSTA)

作者： Seric, Ljiljana Krstinic, Damir Braovic, Maja Milatic, Ivan Mircevski, Aljosa Stipanicev, Darko Univ Split Fac Elect Engn Mech Engn & Naval Architecture Rudera Boskovica 32 Split 210000 Croatia

ISBN: (纸本)9783319398839;9783319398822

In this paper we describe holonic organization of a multi agent system for automatic vehicle classification in a road toll system. Classification of vehicles in road toll systems is based on physical vehicle features and in this paper we focus on axle counting as the first discriminant feature for class determination. Our system relies on two main sensors-video camera and depth sensor. Video image and depth image processing is performed in several holons. The results from individual holons are fused into the final decision on a number of axles of a passing vehicle. We show that fusion of results from individual holons givesmore precise results than individual holons. Holonic organization of the system aids scalability and simplifies inclusion of new sensors and new algorithms.

关键词： Holonic MAS Vehicle classification Image processing Data fusion

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Proceedings - WiSEE 2016: 2016 IEEE International conference on Wireless for Space and Extreme Environments

Proceedings - WiSEE 2016: 2016 IEEE International Conference...

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2016 IEEE International conference on Wireless for Space and Extreme Environments, WiSEE 2016

ISBN: (纸本)9781509026098

The proceedings contain 37 papers. The topics discussed include: Llifetime and power consumption optimization for distributed passive radar systems;partial distributed beamforming design in passive radar sensor networks;power allocation for multi-target multi-fusion-rule sensor networks;efficient set-membership filtering algorithms for wireless sensor networks;low power ASIC design for infrared sensor network inside Arianne 5 vehicle equipment bay;a measurement-based trajectory model for drifted motions towards a target zone;stochastic model for data center energy saving augmented by optical wireless links;reducing energy consumption of data centers using optical wireless links;1-D array of silicon nitride grating couplers for visible light communications;adaptive real-time software defined MIMO visible light communications using spatial multiplexing and spatial diversity;utility of light emitting diodes for inter-satellite communication in multi-satellite networks;internetworking approaches towards along-track segmented satellite architectures;deployment of a wireless sensor network in assembly, integration and test activities;and a 4-elements performance analysis of compact UWB antenna for MIMO-OFDM systems.

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TAU-FIVE: a Multi-Tiered Architecture for Data Quality and Energy-Sustainability in sensor Networks 12

TAU-FIVE: a Multi-Tiered Architecture for Data Quality and E...

引用

12th IEEE Annual International conference on Distributed Computing in sensor Systems (DCOSS)

作者： Lawson, Victor J. Ramaswamy, Lakshmish Univ Georgia Dept Comp Sci Athens GA 30602 USA

ISBN: (纸本)9781509014590

Current research on wireless sensor networks "WSNs" in the Internet of Things "IoT" has focused on performance, scalability and energy efficiency. Innovations in these areas have many challenges due to the increasing volume of smart device data streams in the internet of Everything "IoE". Data feeds from future IoE systems such as the internet of vehicles, smart homes and smart-cities will need real time consolidation. This merger of technologies will require innovative big data algorithms and architectures that authenticate the data streams. A primary concern is in dynamically quantifying the data quality "DQ" of the streams while constructing real-time metrics to assess the energy efficiency "EE" of these IoE devices. In order to define the relationship between sensor stream DQ and EE, we propose our multi-tiered cloud-service architecture TAU-FIVE. The technical contributions of our framework includes data quality and energy efficiency models based on 7 DQ attributes and multiple reprogrammable smart sensors that dynamically modify and regulate the DQ and EE of a WSN. Our research maintains that WSN's can balance sustainability with quality of service by creating real-time metrics that merge energy usage with data stream integrity. This equilibrium will impact energy awareness in the IoT as the multitude of batch device data streams are integrated with the variety of social and professional networks and evolve into the IoE.

关键词： Data quality cloud computing energy model applications to sensing green networks

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Energy-Efficient Fuzzy Logic Cluster Head selection in Wireless sensor Networks

Energy-Efficient Fuzzy Logic Cluster Head selection in Wirel...

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International conference on Information Technology for Organizations Development (IT4OD)

作者： El Alami, Hassan Najid, Abdellah Natl Inst Posts & Telecommun INPT STRS Lab Rabat Morocco

ISBN: (纸本)9781467376891

WSNs are characterized by limited energy constraints. This characteristic poses considerable challenge on design of routing protocols. Therefore, many designers and researchers focus on architectures and algorithms that allow energy-efficient operation of WSNs. One of the popular algorithms in this regard is clustering algorithm. Thus, there are many routing protocols based on clustering algorithm has been proposed for WSNs, the functionality of these protocols is divided into cluster heads (CHs) selection and cluster formation. However, CHs selection is one of the very important problems in routing protocols applications and can drastically impact the network lifespan thereby energy conservation task for WSNs. In this paper, we propose a new routing approach called Energy-efficient fuzzy logic cluster head (EEFL-CH);it is an improvement of LEACH protocol. The goal of this approach is to decrease energy consumption in terms of network lifetime extension using three fuzzy parameters. These parameters are residual energy, expected efficiency, and closeness to base station. Simulation results show that EEFL-CH approach has the better result as compared with LEACH and LEACH-ERE routing protocols.

关键词： cluster head LEACH LEACH-ERE fuzzy logic wireless sensor networks energy-efficient

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Low Cost Inertial Measurement Unit for Motion Capture in Biomedical applications 7th

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7th IFIP WG 5.5/SOCOLNET Advanced Doctoral conference on Computing, Electrical and Industrial Systems (DoCEIS)

作者： Lourenco, Joao Martins, Leonardo Almeida, Rui Quaresma, Claudia Vieira, Pedro Univ Nova Lisboa Fac Ciencias & Tecnol Dept Phys LIBPhys UNL P-2829516 Monte De Caparica Portugal Univ Nova Lisboa Inst Dev New Technol P-2829516 Caparica Portugal Univ Nova Lisboa Fac Ciencias & Tecnol Dept Phys LIBPhys P-2829516 Monte De Caparica Portugal

ISBN: (纸本)9783319311654;9783319311647

A low-cost inertial measurement unit has been developed for accurate motion capture, allowing real-time spatial position registration (linear and angular) of the user's whole-body. For this, we implemented a dedicated circuit for 9 degrees of freedom motion sensors, composed of an accelerometer, gyroscope and a magnetometer. We also applied signal processing and data fusion algorithms to prevent the inherent drift of the position signal. This drift is known to exist during the sensor integration process and the implemented algorithms showed promising results. This system is meant to be used in two specific biomedical applications. The first one is linked to the development of a low-cost system for gait analysis of the whole-body, which can be used in home-based rehabilitation systems. The second application is related to the real-time analysis of working postures and the identification of ergonomic risk factors for musculoskeletal disorders.

关键词： Motion capture sensor fusion Cyber-physical systems Home rehabilitation Work risk analysis

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