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Moving motion estimation from encoder for low-complexity video sensors
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Digital Media Lab)
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this paper we present an approach to provide efficient low-complexity video encoding for wireless sensor networks. We present an method based on removing the most time-consuming task, that is motion estimation, from the encoder. Instead the decoder will perform motion prediction based on the available decoded frame and send the predicted motion vectors to the encoder. We present results based on a modified H.264 implementation. Our results shows that this approach can provide rather good coding efficiency even for relatively high network delays.

URN: urn:nbn:se:umu:diva-38023OAI: diva2:371828
To be submittedAvailable from: 2010-11-23 Created: 2010-11-22 Last updated: 2010-11-23Bibliographically approved
In thesis
1. Wireless video sensor network and its applications in digital zoo
Open this publication in new window or tab >>Wireless video sensor network and its applications in digital zoo
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Most computing and communicating devices have been personal computers that were connected to Internet through a fixed network connection. It is believed that future communication devices will not be of this type. Instead the intelligence and communication capability will move into various objects that surround us. This is often referred to as the "Internet of Things" or "Wireless Embedded Internet". This thesis deals with video processing and communication in these types of systems.

One application scenario that is dealt with in this thesis is real-time video transmission over wireless ad-hoc networks. Here a set of devices automatically form a network and start to communicate without the need for any previous infrastructure. These devices act as both hosts and routers and can build up large networks where they forward information for each other. We have identified two major problems when sending real-time video over wireless ad-hoc networks. One is the reactive design used by most ad-hoc routing protocols. When nodes move some links that are used in the communication path between the sender and the receiver may disappear. The reactive routing protocols wait until some links on the path breaks and then start to search for a new path. This will lead to long interruptions in packet delivery and does not work well for real-time video transmission. Instead we propose an approach where we identify when a route is about to break and start to search for new routes before this happen. This is called a proactive approach. Another problem is that video codecs are very sensitive for packet losses and at the same time the wireless ad-hoc network is very error prone. The most common way to handle lost packets in video codecs is to periodically insert frames that are not predictively coded. This method periodically corrects errors regardless there has been an error or not. The method we propose is to insert frames that are not predictively coded directly after a packet has been lost, and only if a packet has been lost.

Another area that is dealt with in this thesis is video sensor networks. These are small devices that have communication and computational capacity, they are equipped with an image sensor so that they can capture video. Since these devices in general have very limited resources in terms of energy, computation, communication and memory they demand a lot of the video compression algorithms used. In standard video compression algorithms the complexity is high for the encoder while the decoder has low complexity and is just passively controlled by the encoder. We propose video compression algorithms for wireless video sensor networks where complexity is reduced in the encoder by moving some of the image analysis to the decoder side. We have implemented our approach on actual low-power sensor nodes to test our developed algorithms.

Finally we have built a "Digital Zoo" that is a complete system including a large scale outdoor video sensor network. The goal is to use the collected data from the video sensor network to create new experiences for physical visitors in the zoo, or "cyber" visitors from home. Here several topics that relate to practical deployments of sensor networks are addressed.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2010. 56 p.
Digital Media Lab, ISSN 1652-6295 ; 13
Wireless Sensor Networks, Wireless ad-hoc Networks, Digital Zoo, Video Compression, Real-Time Video Communication, Object Tracking, Sensor Fusion
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Signal Processing
urn:nbn:se:umu:diva-38032 (URN)978-91-7459-116-3 (ISBN)
Public defence
2010-12-14, Teknikhuset, A305, Umeå universitet, Umeå, 10:00 (English)
Available from: 2010-11-23 Created: 2010-11-22 Last updated: 2010-11-23Bibliographically approved

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