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O'Nils, Mattias
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Publications (10 of 141) Show all publications
Aurangzeb, K., Alhussein, M. & O'Nils, M. (2018). Analysis of Binary Image Coding Methods for Outdoor Applications of Wireless Vision sensor Networks. IEEE Access, 6, 16932-16941
Open this publication in new window or tab >>Analysis of Binary Image Coding Methods for Outdoor Applications of Wireless Vision sensor Networks
2018 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 16932-16941Article in journal (Refereed) Published
Abstract [en]

The processing of images at the vision sensor nodes (VSN) requires a high computation power and their transmission requires a large communication bandwidth. The energy budget is limited in outdoor applications of wireless vision sensor networks (WVSN). This means that both the processing of images at the VSN and the communication to server must be energy efficient. The wireless communication of uncompressed data consumes huge amounts of energy. Data compression methods are efficient in reducing data in images and can be used for the reduction in transmission energy. We have evaluated seven binary image coding techniques. Our evaluation is based on the processing complexity and energy consumption of the compression methods on the embedded platforms. The focus is to come up with a binary image coding method, which has good compression efficiency and short processing time. An image coding method with such attributes will result in reduced total energy requirement of the node. We have used both statistically generated images and real captured images, in our experiments. Based on our results, we conclude that International Telegraph and Telephone Consultative Committee Group 4, gzip_pack and JPEG-LS are suitable coding methods for the outdoor applications of WVSNs.

Keywords
Embedded systems, energy consumption, image compression, wireless vision sensor network
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-33623 (URN)10.1109/ACCESS.2018.2816162 (DOI)000430436500001 ()
Available from: 2018-05-15 Created: 2018-05-15 Last updated: 2018-05-15Bibliographically approved
Shallari, I., Krug, S. & O'Nils, M. (2018). Architectural evaluation of node: server partitioning for people counting. In: ICDSC '18 Proceedings of the 12th International Conference on Distributed Smart Cameras: . Paper presented at International Conference on Distributed Smart Cameras. Ney York: ACM Digital Library, Article ID Article No. 1.
Open this publication in new window or tab >>Architectural evaluation of node: server partitioning for people counting
2018 (English)In: ICDSC '18 Proceedings of the 12th International Conference on Distributed Smart Cameras, Ney York: ACM Digital Library, 2018, article id Article No. 1Conference paper, Published paper (Refereed)
Abstract [en]

The Internet of Things has changed the range of applications for cameras requiring them to be easily deployed for a variety of scenarios indoor and outdoor, while achieving high performance in processing. As a result, future projections emphasise the need for battery operated smart cameras, capable of complex image processing tasks that also communicate within one another, and the server. Based on these considerations, we evaluate in-node and node – server configurations of image processing tasks to provide an insight of how tasks partitioning affects the overall energy consumption. The two main energy components taken in consideration for their influence in the total energy consumption are processing and communication energy. The results from the people counting scenario proved that processing background modelling, subtraction and segmentation in-node while transferring the remaining tasks to the server results in the most energy efficient configuration, optimising both processing and communication energy. In addition, the inclusion of data reduction techniques such as data aggregation and compression not always resulted in lower energy consumption as generally assumed, and the final optimal partition did not include data reduction.

Place, publisher, year, edition, pages
Ney York: ACM Digital Library, 2018
Keywords
Image processing, people counting, smart camera, WVSN, thermography
National Category
Embedded Systems Signal Processing
Identifiers
urn:nbn:se:miun:diva-34613 (URN)10.1145/3243394.3243688 (DOI)978-1-4503-6511-6 (ISBN)
Conference
International Conference on Distributed Smart Cameras
Available from: 2018-10-03 Created: 2018-10-03 Last updated: 2018-10-04Bibliographically approved
Shallari, I., Anwar, Q., Imran, M. & O'Nils, M. (2018). Background Modelling, Analysis and Implementation for Thermographic Images. In: PROCEEDINGS OF THE 2017 SEVENTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA 2017): . Paper presented at Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA 2017), Montreal, Canada; November 28 - December 1, 2017. IEEE
Open this publication in new window or tab >>Background Modelling, Analysis and Implementation for Thermographic Images
2018 (English)In: PROCEEDINGS OF THE 2017 SEVENTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA 2017), IEEE, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Background subtraction is one of the fundamental steps in the image-processing pipeline for distinguishing foreground from background. Most of the methods have been investigated with respect to visual images, in which case challenges are different compared to thermal images. Thermal sensors are invariant to light changes and have reduced privacy concerns. We propose the use of a low-pass IIR filter for background modelling in thermographic imagery due to its better performance compared to algorithms such as Mixture of Gaussians and K-nearest neighbour, while reducing memory requirements for implementation in embedded architectures. Based on the analysis of four different image datasets both indoor and outdoor, with and without people presence, the learning rate for the filter is set to 3×10-3 Hz and the proposed model is implemented on an Artix-7 FPGA.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Infrared; visual; pedestrian detection; smart camera; architecture; surveillance.
National Category
Embedded Systems
Identifiers
urn:nbn:se:miun:diva-32445 (URN)10.1109/IPTA.2017.8310078 (DOI)000428743900002 ()2-s2.0-85050756650 (Scopus ID)978-1-5386-1842-4 (ISBN)
Conference
Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA 2017), Montreal, Canada; November 28 - December 1, 2017
Projects
City Movements
Available from: 2017-12-13 Created: 2017-12-13 Last updated: 2018-10-01Bibliographically approved
Shahzad, K. & O'Nils, M. (2018). Condition Monitoring in Industry 4.0-Design Challenges and Possibilities: A Case Study. In: 2018 Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2018 - Proceedings: . Paper presented at 2018 Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2018, Brescia, Italy, 16 April 2018 through 18 April 2018 (pp. 101-106). IEEE, Article ID 8428306.
Open this publication in new window or tab >>Condition Monitoring in Industry 4.0-Design Challenges and Possibilities: A Case Study
2018 (English)In: 2018 Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2018 - Proceedings, IEEE, 2018, p. 101-106, article id 8428306Conference paper, Published paper (Refereed)
Abstract [en]

The application of IoT in manufacturing industry is believed to transform the traditional concept of factories into fully integrated manufacturing systems that are capable of meeting different requirements/demands originating within the factory, in supply chain and in user communities in a real time manner. One key area that is likely to benefit at an early stage development of the Industrial IoT is the condition monitoring of the production machinery. However, there are several challenges in realizing effective IoT enabled condition monitoring solutions with currently available enabling technologies. In this paper, we analyze the design challenges associated with realizing IoT enabled industrial condition monitoring with particular focus on enabling end-devices in managing large amount of acquired data. With the help of a vibration based condition monitoring case study the challenges are analyzed in a quantitative manner and possible alternatives are explored. The results suggest that for the efficient and long term condition monitoring in the smart industry of the future, improvements in the enabling technologies are required to design optimized end-devices. 

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Condition Monitoring, IIoT, Industrial health monitoring, Industry 4.0, IoT
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-34594 (URN)10.1109/METROI4.2018.8428306 (DOI)2-s2.0-85052495027 (Scopus ID)9781538624975 (ISBN)
Conference
2018 Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2018, Brescia, Italy, 16 April 2018 through 18 April 2018
Available from: 2018-10-03 Created: 2018-10-03 Last updated: 2018-10-03Bibliographically approved
Alqaysi, H., Lawal, N., Fedorov, I. & O'Nils, M. (2018). Full Coverage Optimization for Multi Camera Dome Placement in Volumetric Monitoring. In: ICDSC '18 Proceedings of the 12th International Conference on Distributed Smart Cameras: . Paper presented at International Conference on Distributed Smart Cameras. New York, NY, USA: ACM Digital Library, Article ID Article No. 2.
Open this publication in new window or tab >>Full Coverage Optimization for Multi Camera Dome Placement in Volumetric Monitoring
2018 (English)In: ICDSC '18 Proceedings of the 12th International Conference on Distributed Smart Cameras, New York, NY, USA: ACM Digital Library, 2018, article id Article No. 2Conference paper, Published paper (Refereed)
Abstract [en]

Volumetric monitoring can be challenging due to having a 3D target space and moving objects within it. Multi camera dome is proposed to provide a hemispherical coverage of the 3D space around it. This paper introduces a method that optimizes multi camera placement for full coverage in volumetric monitoring system. Camera dome placement is modeled in a volume by adapting the hexagonal packing of circles to provide full coverage at a given height, and 100% detection of flying objects within it. The coverage effectiveness of different placement configurations was assessed using an evaluation environment. The proposed placement is applicable in designing and deploying surveillance systems for remote outdoor areas, such as sky monitoring in wind farms and airport runways in order to record and analyze flying activities.

Place, publisher, year, edition, pages
New York, NY, USA: ACM Digital Library, 2018
Keywords
Volumetric surveillance, sky monitoring, camera dome, placement optimization.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:miun:diva-34589 (URN)10.1145/3243394.3243690 (DOI)978-1-4503-6511-6 (ISBN)
Conference
International Conference on Distributed Smart Cameras
Projects
SMART
Available from: 2018-10-02 Created: 2018-10-02 Last updated: 2018-10-03Bibliographically approved
Fedorov, I., Lawal, N., Thörnberg, B., Alqaysi, H. & O'Nils, M. (2018). Towards calibration of outdoor multi-camera visual monitoring system. In: : . Paper presented at ICDSC'18 Proceedings of the 12th International Conference on Distributed Smart Cameras. New York, NY, US: ACM Digital Library
Open this publication in new window or tab >>Towards calibration of outdoor multi-camera visual monitoring system
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a method for calibrating of multi-camera systems where no natural reference points exist in the surrounding environment. Monitoring the air space at wind farms is our test case. The goal is to monitor the trajectories of flying birds to prevent them from colliding with rotor blades. Our camera calibration method is based on the observation of a portable artificial reference marker made out of a pulsed light source and a navigation satellite sensor module. The reference marker can determine and communicate its position in the world coordinate system at centimeter precision using navigartion sensors. Our results showed that simultaneous detection of the same marker in several cameras having overlapping field of views allowed us to determine the markers position in 3D world coordinate space with an accuracy of 3-4 cm. These experiments were made in the volume around a wind turbine at distances from cameras to marker within a range of 70 to 90 m.

Place, publisher, year, edition, pages
New York, NY, US: ACM Digital Library, 2018. p. 6
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-34643 (URN)10.1145/3243394.3243695 (DOI)978-1-4503-6511-6 (ISBN)
Conference
ICDSC'18 Proceedings of the 12th International Conference on Distributed Smart Cameras
Available from: 2018-10-05 Created: 2018-10-05 Last updated: 2018-10-09Bibliographically approved
Alqaysi, H., Lawal, N., Fedorov, I. & O'Nils, M. (2017). Evaluating Coverage Effectiveness of Multi-Camera Domes Placement for Volumetric Surveillance. In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras: . Paper presented at The 11th International Conference on Distributed Smart Cameras (ICDSC), Stanford University, Stanford; United States; 5 September 2017 through 7 September 2017 (pp. 49-54). New York, NY, USA: Association for Computing Machinery (ACM), F132201
Open this publication in new window or tab >>Evaluating Coverage Effectiveness of Multi-Camera Domes Placement for Volumetric Surveillance
2017 (English)In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras, New York, NY, USA: Association for Computing Machinery (ACM), 2017, Vol. F132201, p. 49-54Conference paper, Published paper (Refereed)
Abstract [en]

Multi-camera dome is composed of a number of cameras arranged to monitor a half sphere of the sky. Designing a network of multi-camera domes can be used to monitor flying activities in open large area, such as birds' activities in wind parks. In this paper, we present a method for evaluating the coverage effectiveness of the multi-camera domes placement in such areas. We used GPS trajectories of free flying birds over an area of 9 km2 to analyze coverage effectiveness of randomly placed domes. The analysis is based on three criteria namely, detection, positioning and the maximum resolution captured. The developed method can be used to evaluate results of designing and optimizing dome placement algorithms for volumetric monitoring systems in order to achieve maximum coverage.

Place, publisher, year, edition, pages
New York, NY, USA: Association for Computing Machinery (ACM), 2017
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-32311 (URN)10.1145/3131885.3131916 (DOI)2-s2.0-85038865753 (Scopus ID)978-1-4503-5487-5 (ISBN)
Conference
The 11th International Conference on Distributed Smart Cameras (ICDSC), Stanford University, Stanford; United States; 5 September 2017 through 7 September 2017
Projects
SMART
Available from: 2017-12-07 Created: 2017-12-07 Last updated: 2018-01-26Bibliographically approved
Shallari, I., Imran, M., O'Nils, M. & Lawal, N. (2017). Evaluating Pre-Processing Pipelines for Thermal-Visual Smart Camera. In: Proceedings of the 11th International Conference on Distributed Smart Cameras: . Paper presented at 11th International Conference on Distributed Smart Cameras, Stanford University, Stanford; United States; 5 September 2017 through 7 September 2017 (pp. 95-100). ACM Digital Library, F132201
Open this publication in new window or tab >>Evaluating Pre-Processing Pipelines for Thermal-Visual Smart Camera
2017 (English)In: Proceedings of the 11th International Conference on Distributed Smart Cameras, ACM Digital Library, 2017, Vol. F132201, p. 95-100Conference paper, Published paper (Refereed)
Abstract [en]

Smart camera systems integrating multi-model image sensors provide better spectral sensitivity and hence better pass-fail decisions. In a given vision system, pre-processing tasks have a ripple effect on output data and pass-fail decision of high level tasks such as feature extraction, classification and recognition. In this work, we investigated four pre-processing pipelines and evaluated the effect on classification accuracy and output transmission data. The pre-processing pipelines processed four types of images, thermal grayscale, thermal binary, visual and visual binary. The results show that the pre-processing pipeline, which transmits visual compressed Region of Interest (ROI) images, offers 13 to 64 percent better classification accuracy as compared to thermal grayscale, thermal binary and visual binary. The results show that visual raw and visual compressed ROI with suitable quantization matrix offers similar classification accuracy but visual compressed ROI offers up to 99 percent reduced communication data as compared to visual ROI.

Place, publisher, year, edition, pages
ACM Digital Library, 2017
Keywords
Thermal imaging, FPGA, intelligence partitioning
National Category
Embedded Systems
Identifiers
urn:nbn:se:miun:diva-32437 (URN)10.1145/3131885.3131908 (DOI)2-s2.0-85038877488 (Scopus ID)978-1-4503-5487-5 (ISBN)
Conference
11th International Conference on Distributed Smart Cameras, Stanford University, Stanford; United States; 5 September 2017 through 7 September 2017
Projects
SMART
Funder
Knowledge Foundation
Available from: 2017-12-13 Created: 2017-12-13 Last updated: 2018-01-30Bibliographically approved
Anwar, Q., Imran, M. & O'Nils, M. (2017). Intelligence Partitioning as a Method for Architectural Exploration of Wireless Sensor Node. In: Proceedings of the International Conference on Computational Science and Computational Intelligence (CSCI), 2016.: . Paper presented at 2016 International Conference on Computational Science and Computational Intelligence, 15-17 Dec. 2016, Las Vegas, NV, USA (pp. 935-940). IEEE Press, Article ID 7881473.
Open this publication in new window or tab >>Intelligence Partitioning as a Method for Architectural Exploration of Wireless Sensor Node
2017 (English)In: Proceedings of the International Conference on Computational Science and Computational Intelligence (CSCI), 2016., IEEE Press, 2017, p. 935-940, article id 7881473Conference paper, Published paper (Refereed)
Abstract [en]

Embedded systems with integrated sensing, processing and wireless communication are driving future connectivity concepts such as Wireless Sensor Networks (WSNs) and Internet of Things (IoTs). Because of resource limitations, there still exists a number of challenges such as low latency and energy consumption to realize these concepts to full potential. To address and understand these challenges, we have developed and employed an intelligence partitioning method which generates different implementation alternatives by distributing processing load across multiple nodes. The task-to-node mapping has exponential complexity which is hard to compute for a large scale system. Regarding this, our method provides recommendation to handle and minimize such complexity for a large system. Experiments on a use-case concludes that the proposed method is able to identify unfavourable architecture solutions in which forward and backword communication paths exists in task-to-node mapping. These solution can be avoided for further architectural exploration, thus limiting the space for architecture exploration of a sensor node.

Place, publisher, year, edition, pages
IEEE Press, 2017
Keywords
Edge computing, intelligence partitioning, embedded computing
National Category
Computer Systems
Identifiers
urn:nbn:se:miun:diva-30736 (URN)10.1109/CSCI.2016.0180 (DOI)000405582400172 ()2-s2.0-85017325247 (Scopus ID)STC (Local ID)978-1-5090-5510-4 (ISBN)STC (Archive number)STC (OAI)
Conference
2016 International Conference on Computational Science and Computational Intelligence, 15-17 Dec. 2016, Las Vegas, NV, USA
Projects
ASISSMART
Funder
Knowledge Foundation
Available from: 2017-05-16 Created: 2017-05-16 Last updated: 2017-10-12Bibliographically approved
Fedorov, I., Lawal, N., O'Nils, M. & Alqaysi, H. (2017). Placement Strategy of Multi-Camera Volumetric Surveillance System for Activities Monitoring. In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras: . Paper presented at The 11th International Conference on Distributed Smart Cameras (ICDSC), Stanford University Stanford; United States; 5 September 2017 through 7 September 2017 (pp. 113-118). New York, NY, USA: Association for Computing Machinery (ACM), F132201
Open this publication in new window or tab >>Placement Strategy of Multi-Camera Volumetric Surveillance System for Activities Monitoring
2017 (English)In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras, New York, NY, USA: Association for Computing Machinery (ACM), 2017, Vol. F132201, p. 113-118Conference paper, Published paper (Refereed)
Abstract [en]

The design of multi-camera surveillance system comes with many advantages, for example it facilitates as understanding how flying objects act in a given volume. One possible application is for the observation interaction of birds and calculate their trajectories around wind turbines to create promising systems for preventing bird collisions with turbine blades. However, there are also challenges, such as finding the optimal node placement and camera calibration. To address these challenges we investigated a trade-off between calibration accuracy and node requirements, including resolution, modulation transfer function, field of view and angle baseline. We developed a strategy for camera placement to achieve improved coverage for golden eagle monitoring and tracking. This strategy based on the modified resolution criterion taking into account the contrast function of the camera and the estimation of the base angle between the cameras.

Place, publisher, year, edition, pages
New York, NY, USA: Association for Computing Machinery (ACM), 2017
Keywords
Multi-camera, outdoor monitoring, placement, camera calibration
National Category
Computer Systems Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-32726 (URN)10.1145/3131885.3131911 (DOI)2-s2.0-85038856097 (Scopus ID)978-1-4503-5487-5 (ISBN)
Conference
The 11th International Conference on Distributed Smart Cameras (ICDSC), Stanford University Stanford; United States; 5 September 2017 through 7 September 2017
Projects
SMART
Available from: 2018-01-23 Created: 2018-01-23 Last updated: 2018-01-26Bibliographically approved
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