Hive: A distributed system for vision processing

Afrah, Amir; Miller, Gregor; Parks, Donovan H.; Finke, Matthias; Fels, Sidney

doi:10.1109/icdsc.2008.4635724

Cited by 16 publications

(11 citation statements)

References 10 publications

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“…Under this classification we present UCF as a solution to the Access problem. The other components in the computer vision pipeline have various example solutions, such as Hive [2] for transfer, ImageMagick for conversion and CoreImage TM for modification (although these last two also expand out of our defined scope). As yet there are no known solutions to the Analysis problem which limit their scope to analysis while also being comprehensive and accessible to those not specialised in computer vision techniques.…”

Section: Analysementioning

confidence: 99%

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Uniform image and camera access

Miller

Fels

2009

2009 Workshop on Applications of Computer Vision (WACV)

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We introduce a work-in-progress camera access scheme we call the Unified Camera Framework. Attempts have been made in the past to provide simple access to cameras, however these are generally OS specific or lacking in functionality. We present a novel interface which works across operating systems, and provides access to native images through a descriptor. A unified configuration model is presented to allow manipulation of camera parameters to the level each camera supports. Validation of the ideas presented is given in the form of a proof-of-concept implementation called the All Seeing Eye.

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Section: Analysementioning

confidence: 99%

“…To access cameras across the network we chose to use the freely available vision transport system Hive [2] as the underlying network layer for ASE. Currently we can use the interface to access cameras on other machines using a hostname and port combination, and each camera on every machine has its own small server.…”

Section: Example Implementationmentioning

confidence: 99%

Uniform image and camera access

Miller

Fels

2009

2009 Workshop on Applications of Computer Vision (WACV)

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“…HIVE [11] creates pipelines called "swarms" out of single elements called "drones" where each drone is executed in its own thread. Synchronised and streaming data transfer models are provided to transmit data from one drone to another.…”

Section: Related Workmentioning

confidence: 99%

Reducing Processing Delay in Dataflow-oriented Middleware Systems for Smart Camera Applications

Guggi

Rinner

2014

Proceedings of the International Conference on Distributed Smart Cameras

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Dataflow-oriented processing is an attractive paradigm for smart camera applications. In this paper we present a datafloworiented middleware system to support the development of such applications on resource-limited distributed systems. Our main contribution includes the reduction of the overall processing delay by delaying the data generation and by the just-in-time transfer of data elements. A side effect of this delayed data transfer is also a reduction of the memory requirement for the communication links. We introduce the basic algorithm and present experimental results of our middleware system running in a distributed environment.

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“…In [10] the HIVE middleware is presented that supports the formation of vision processing pipelines. Basic components or services are called drones which can be composed to form applications called swarms.…”

Section: Related Workmentioning

confidence: 99%

A pervasive smart camera network architecture applied for multi-camera object classification

Schriebl

Winkler

Starzacher

et al. 2009

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)

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Abstract-Visual sensor networks are an emerging research area with the goal of using cameras as pervasive and affordable sensing and processing devices. This paper presents a pervasive smart camera platform which is built from off-the-shelf hardware and software components. The hardware platform is comprised of an OMAP 3530 processor, 128 MB RAM and various interfaces for connecting sensors and peripherals. A dual-radio wireless network allows to trade communication performance for power consumption. The software architecture is built upon standard Linux and supports dataflow oriented application development by dynamically instantiating and connecting functions blocks. Data is transferred between blocks via shared memory for high throughput. We present a performance evaluation of our smart camera platform as well as a multi-camera object classification system to demonstrate the capabilities and applicability of our approach.

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Hive: A distributed system for vision processing

Cited by 16 publications

References 10 publications

Uniform image and camera access

Uniform image and camera access

Reducing Processing Delay in Dataflow-oriented Middleware Systems for Smart Camera Applications

A pervasive smart camera network architecture applied for multi-camera object classification

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