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Distributed coding/decoding complexity in video sensor networks.

Cordeiro PJ, Assunção P - Sensors (Basel) (2012)

Bottom Line: Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate.Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted.The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

View Article: PubMed Central - PubMed

Affiliation: Instituto Politécnico de Leiria/ESTG, Alto Vieiro, Leiria, Portugal. paulo.cordeiro@ipleiria.pt

ABSTRACT
Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

No MeSH data available.


Related in: MedlinePlus

Transcoding gateway.
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f5-sensors-12-02693: Transcoding gateway.

Mentions: The general architecture of the transcoding gateway is shown in Figure 5. It is comprised of a cascade of decoder-encoder where each one has specific functionalities that enable management of the computational complexity allocated to the video sensor and mobile decoder, to a certain extent. In the case of the video sensor, the encoding algorithm may skip the motion estimation function (either totally or partially) in order to reduce the computational complexity required at the sensor device. As a consequence the transmitted bit rate is also lower than in the case where motion vectors are sent in the coded stream. Then the decoder of the transcoding gateway must implement the same motion estimation function as the encoder of the video sensor, in order to build the same predictions as those used for encoding. Recent work has shown that motion estimation can be efficiently performed at the decoder [36,37]. Either decoder-side motion vector derivation or decoder-side motion estimation can lead to significant reduction in coding rate and at the same time transferring part of the computational complexity from the encoder to the decoder. Therefore, this transcoding process is equivalent to transferring a significant part of the encoding complexity from the video sensor to the transcoding gateway, which is beneficial to the sensor and to the transmission efficiency without any problem to the gateway, because this is wired powered equipment without major computational or energy constraints. It is worthwhile to notice that such a video coding scheme is not compliant with any currently available standard, but this is not a problem because the communication between the VSN nodes and the transcoding gateway do not need to be standard compliant. Compatibility is only necessary between transcoding and the video sensors, which means that manufacturers of video sensors must also provide a compatible transcoder, which can be built as a standalone system-on-chip and integrated in different types of equipment.


Distributed coding/decoding complexity in video sensor networks.

Cordeiro PJ, Assunção P - Sensors (Basel) (2012)

Transcoding gateway.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376628&req=5

f5-sensors-12-02693: Transcoding gateway.
Mentions: The general architecture of the transcoding gateway is shown in Figure 5. It is comprised of a cascade of decoder-encoder where each one has specific functionalities that enable management of the computational complexity allocated to the video sensor and mobile decoder, to a certain extent. In the case of the video sensor, the encoding algorithm may skip the motion estimation function (either totally or partially) in order to reduce the computational complexity required at the sensor device. As a consequence the transmitted bit rate is also lower than in the case where motion vectors are sent in the coded stream. Then the decoder of the transcoding gateway must implement the same motion estimation function as the encoder of the video sensor, in order to build the same predictions as those used for encoding. Recent work has shown that motion estimation can be efficiently performed at the decoder [36,37]. Either decoder-side motion vector derivation or decoder-side motion estimation can lead to significant reduction in coding rate and at the same time transferring part of the computational complexity from the encoder to the decoder. Therefore, this transcoding process is equivalent to transferring a significant part of the encoding complexity from the video sensor to the transcoding gateway, which is beneficial to the sensor and to the transmission efficiency without any problem to the gateway, because this is wired powered equipment without major computational or energy constraints. It is worthwhile to notice that such a video coding scheme is not compliant with any currently available standard, but this is not a problem because the communication between the VSN nodes and the transcoding gateway do not need to be standard compliant. Compatibility is only necessary between transcoding and the video sensors, which means that manufacturers of video sensors must also provide a compatible transcoder, which can be built as a standalone system-on-chip and integrated in different types of equipment.

Bottom Line: Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate.Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted.The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

View Article: PubMed Central - PubMed

Affiliation: Instituto Politécnico de Leiria/ESTG, Alto Vieiro, Leiria, Portugal. paulo.cordeiro@ipleiria.pt

ABSTRACT
Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

No MeSH data available.


Related in: MedlinePlus