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- Karlsson, Johannes, 1977-
(författare)
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Wireless video sensor network and its applications in digital zoo
- 2010
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Doktorsavhandling (övrigt vetenskapligt)abstract
- 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.
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| 2. |
- Söderström, Ulrik, 1978-
(författare)
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Very low bitrate facial video coding
- 2006
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Licentiatavhandling (övrigt vetenskapligt)abstract
- This thesis introduces a coding scheme for very low bitrate video coding through the aid of principal component analysis. Principal information of the facial mimic for a person can be extracted and stored in an Eigenspace. Entire video frames of this persons face can then be compressed with the Eigenspace to only a few projection coefficients. Principal component video coding encodes entire frames at once and increased frame size does not increase the necessary bitrate for encoding, as standard coding schemes do. This enables video communication with high frame rate, spatial resolution and visual quality at very low bitrates. No standard video coding technique provides these four features at the same time.Theoretical bounds for using principal components to encode facial video sequences are presented. Two different theoretical bounds are derived. One that describes the minimal distortion when a certain number of Eigenimages are used and one that describes the minimum distortion when a minimum number of bits are used.We investigate how the reconstruction quality for the coding scheme is affected when the Eigenspace, mean image and coefficients are compressed to enable efficient transmission. The Eigenspace and mean image are compressed through JPEG-compression while the while the coefficients are quantized. We show that high compression ratios can be used almost without any decrease in reconstruction quality for the coding scheme.Different ways of re-using the Eigenspace for a person extracted from one video sequence to encode other video sequences are examined. The most important factor is the positioning of the facial features in the video frames.Through a user test we find that it is extremely important to consider secondary workloads and how users make use of video when experimental setups are designed.
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| 3. |
- Söderström, Ulrik, 1978-
(författare)
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Very Low Bitrate Video Communication
- 2008
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Doktorsavhandling (övrigt vetenskapligt)abstract
- A large amount of the information in conversations come from non-verbal cues such as facial expressions and body gesture. These cues are lost when we don't communicate face-to-face. But face-to-face communication doesn't have to happen in person. With video communication we can at least deliver information about the facial mimic and some gestures. This thesis is about video communication over distances; communication that can be available over networks with low capacity since the bitrate needed for video communication is low.A visual image needs to have high quality and resolution to be semantically meaningful for communication. To deliver such video over networks require that the video is compressed. The standard way to compress video images, used by H.264 and MPEG-4, is to divide the image into blocks and represent each block with mathematical waveforms; usually frequency features. These mathematical waveforms are quite good at representing any kind of video since they do not resemble anything; they are just frequency features. But since they are completely arbitrary they cannot compress video enough to enable use over networks with limited capacity, such as GSM and GPRS.Another issue is that such codecs have a high complexity because of the redundancy removal with positional shift of the blocks. High complexity and bitrate means that a device has to consume a large amount of energy for encoding, decoding and transmission of such video; with energy being a very important factor for battery-driven devices.Drawbacks of standard video coding mean that it isn't possible to deliver video anywhere and anytime when it is compressed with such codecs. To resolve these issues we have developed a totally new type of video coding. Instead of using mathematical waveforms for representation we use faces to represent faces. This makes the compression much more efficient than if waveforms are used even though the faces are person-dependent.By building a model of the changes in the face, the facial mimic, this model can be used to encode the images. The model consists of representative facial images and we use a powerful mathematical tool to extract this model; namely principal component analysis (PCA). This coding has very low complexity since encoding and decoding only consist of multiplication operations. The faces are treated as single encoding entities and all operations are performed on full images; no block processing is needed. These features mean that PCA coding can deliver high quality video at very low bitrates with low complexity for encoding and decoding.With the use of asymmetrical PCA (aPCA) it is possible to use only semantically important areas for encoding while decoding full frames or a different part of the frames.We show that a codec based on PCA can compress facial video to a bitrate below 5 kbps and still provide high quality. This bitrate can be delivered on a GSM network. We also show the possibility of extending PCA coding to encoding of high definition video.
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