Limits...
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

Proposed VSN architecture.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3376628&req=5

f4-sensors-12-02693: Proposed VSN architecture.

Mentions: The proposed VSN architecture with distributed complexity control capability is depicted in Figure 4. In such an architecture, there are several clusters of video sensors, interconnected through a mesh network which has some outgoing links to a centralized transcoding gateway. Among other important functionalities, the gateway may perform stream multiplexing and transmission to a core network or Internet, which in turn is used as the core network to deliver the video data to the target receivers. Among many possible receivers that can be used, mobile or portable devices are among those with more stringent limitations in regard to processing power and energy constraints. Therefore, the network architecture takes into account the possibility of having end-user devices with constrained computational complexity in order to achieve extended battery life. This is the case, for instance, of video surveillance applications where remote users can have portable/mobile devices for real-time monitoring of the area of interest. Each cluster of video sensors can be associated with a certain specific application or geographical area, so the architecture is flexible and scalable to fit a wide variety of requirements. As pointed out before, the complexity constraints are mainly located at both extremes of the whole framework, i.e., the video sensors and the end-user terminals. The transcoding gateway is responsible for matching the complexity requirements of both ends.


Distributed coding/decoding complexity in video sensor networks.

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

Proposed VSN architecture.
© Copyright Policy
Related In: Results  -  Collection

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

f4-sensors-12-02693: Proposed VSN architecture.
Mentions: The proposed VSN architecture with distributed complexity control capability is depicted in Figure 4. In such an architecture, there are several clusters of video sensors, interconnected through a mesh network which has some outgoing links to a centralized transcoding gateway. Among other important functionalities, the gateway may perform stream multiplexing and transmission to a core network or Internet, which in turn is used as the core network to deliver the video data to the target receivers. Among many possible receivers that can be used, mobile or portable devices are among those with more stringent limitations in regard to processing power and energy constraints. Therefore, the network architecture takes into account the possibility of having end-user devices with constrained computational complexity in order to achieve extended battery life. This is the case, for instance, of video surveillance applications where remote users can have portable/mobile devices for real-time monitoring of the area of interest. Each cluster of video sensors can be associated with a certain specific application or geographical area, so the architecture is flexible and scalable to fit a wide variety of requirements. As pointed out before, the complexity constraints are mainly located at both extremes of the whole framework, i.e., the video sensors and the end-user terminals. The transcoding gateway is responsible for matching the complexity requirements of both ends.

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