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- Karlsson, Johannes, et al.
(författare)
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Demonstration of Wyner-Ziv video compression in a wireless camera sensor network
- 2009
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Ingår i: The Sixth Swedish National Computer Networking Workshop and Ninth Scandinavian Workshop on Wireless Adhoc Networks (SNCNW+Adhoc 2009).
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Wyner-Ziv video coding can provide low complexity encoding and high complexity decoding and is therefore a promising approach for video coding in wireless sensor networks. We will demonstrate our practical implementation of a wyner-ziv video codec. The hardware platform used in our camera sensor network is the Fleck camera developed by CSIRO ASL in Brisbane, Australia.
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- Karlsson, Johannes, 1977-, et al.
(författare)
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Demonstration of Wyner-Ziv video compression in a wireless camera sensor network
- 2009
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Ingår i: The 9th Scandinavian Workshop on Wireless Ad-hoc & Sensor Networks (ADHOC'09 ). 4-5 May 2009, Uppsala, Sweden.. - Uppsala.
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Konferensbidrag (refereegranskat)abstract
- Sending video over wireless sensor networks is a challenging task. The encoding and transmission of video is very resource hungry and the sensor nodes have very limited resources in terms of communication bandwidth,memory, computation and typically 5-10 times. In this paper we will present a practical implementation of a Wyner-Ziv video codec where the reversed asymmetry in complexity between encoder and decoder can be achieved. We will also present our sensor network platform used in this demonstration known as Fleck TM-3 as well as two different co-processor daughterboards for image processing. The different daughterboards are then compared in terms of speed and energy consumption.
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- Lowry, Stephanie, 1979-, et al.
(författare)
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Visual Place Recognition : A Survey
- 2016
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Ingår i: IEEE Transactions on robotics. - : IEEE Robotics and Automation Society. - 1552-3098 .- 1941-0468. ; 32:1, s. 1-19
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Tidskriftsartikel (refereegranskat)abstract
- Visual place recognition is a challenging problem due to the vast range of ways in which the appearance of real-world places can vary. In recent years, improvements in visual sensing capabilities, an ever-increasing focus on long-term mobile robot autonomy, and the ability to draw on state-of-the-art research in other disciplines - particularly recognition in computer vision and animal navigation in neuroscience - have all contributed to significant advances in visual place recognition systems. This paper presents a survey of the visual place recognition research landscape. We start by introducing the concepts behind place recognition - the role of place recognition in the animal kingdom, how a "place" is defined in a robotics context, and the major components of a place recognition system. Long-term robot operations have revealed that changing appearance can be a significant factor in visual place recognition failure; therefore, we discuss how place recognition solutions can implicitly or explicitly account for appearance change within the environment. Finally, we close with a discussion on the future of visual place recognition, in particular with respect to the rapid advances being made in the related fields of deep learning, semantic scene understanding, and video description.
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- Sjöstrand, Torbjörn, et al.
(författare)
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An introduction to PYTHIA 8.2
- 2015
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Ingår i: Computer Physics Communications. - : Elsevier BV. - 0010-4655. ; 191, s. 159-177
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Tidskriftsartikel (refereegranskat)abstract
- The PYTHIA program is a standard tool for the generation of events in high-energy collisions, comprising a coherent set of physics models for the evolution from a few-body hard process to a complex multiparticle final state. It contains a library of hard processes, models for initial- and final-state parton showers, matching and merging methods between hard processes and parton showers, multiparton interactions, beam remnants, string fragmentation and particle decays. It also has a set of utilities and several interfaces to external programs. PYTHIA 8.2 is the second main release after the complete rewrite from Fortran to C++, and now has reached such a maturity that it offers a complete replacement for most applications, notably for LHC physics studies. The many new features should allow an improved description of data. New version program summary Program title: PYTHIA 8.2 Catalogue identifier: ACTU_v4_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ACTU_v4_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence, version 2 No. of lines in distributed program, including test data, etc.: 478360 No. of bytes in distributed program, including test data, etc.: 14131810 Distribution format: tar.gz Programming language: C++. Computer: Commodity PCs, Macs. Operating system: Linux, OS X; should also work on other systems. RAM: 10 megabytes Classification: 11.2. Does the new version supersede the previous version?: Yes Catalogue identifier of previous version: ACTU_v3_0 Journal reference of previous version: Comput Phys. Comm. 178 (2008) 852 Nature of problem: High-energy collisions between elementary particles normally give rise to complex final states, with large multiplicities of hadrons, leptons, photons and neutrinos. The relation between these final states and the underlying physics description is not a simple one, for two main reasons. Firstly, we do not even in principle have a complete understanding of the physics. Secondly, any analytical approach is made intractable by the large multiplicities. Solution method: Complete events are generated by Monte Carlo methods. The complexity is mastered by a subdivision of the full problem into a set of simpler separate tasks. All main aspects of the events are simulated, such as hard-process selection, initial- and final-state radiation, beam remnants, fragmentation, decays, and so on. Therefore events should be directly comparable with experimentally observable ones. The programs can be used to extract physics from comparisons with existing data, or to. study physics at future experiments. Reasons for new version: Improved and expanded physics models. Summary of revisions: Hundreds of new features and bug fixes, allowing improved modelling. Restrictions: Depends on the problem studied. Running time: 10-1000 events per second, depending on process studied. (C) 2015 Elsevier B.V. All rights reserved.
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- Wark, Tim, et al.
(författare)
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Real-time image streaming over a low-bandwidth wireless camera network
- 2007
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Ingår i: Proceedings of the Third International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2007). 3-6 December 2007, Melbourne, Australia.. ; , s. 113-118
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Konferensbidrag (refereegranskat)abstract
- In this paper we describe the recent development of a low- bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second.
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