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Are there any computer vision algorithms specifically targeting depth images?

Has anyone developed computer vision/image processing algorithms on Twitter Storm?

  • Twitter Storm seems like a good fit for implementing a computer vision algorithm that has real-time requirements, such as querying an image, running an interest point detector, and searching an in-memory data structure of descriptors distributed across multiple machines.  I'm interested in learning if anyone has developed algorithms in the areas of computer vision , image processing using Twitter Storm.  Are there any potential issues that come to mind regarding this?  I saw that uses Storm but in the description I read, they don't seem to be using it in the context of image/video processing. Also if someone knows of an analogous solution that would be good for doing distributed computing with computer vision algorithms, I'd be interested in that as well

  • Answer:

    There is an experimental platform (HIPI) being developed at the University of Virginia for batch image processing you might be interested in looking into: http://hipi.cs.virginia.edu/ We've been successful at integrating the open source OpenCV platform into Hadoop for various image processing applications. With Hadoop 2 + YARN maturing, you have possibility of hybrid architectures for implementing distributed image processing algorithms, e.g. Hadoop+Spark/Storm. There shouldn't be any real roadblocks for implementing a real-time distributed CV application provided you have a good understanding of the mapping vs aggregation steps in a given algorithm, and with that, the IO requirements vis-a-vis CPU- vs Data Volume-intensive components of an algorithm's implementation.

Ashwin Tumne at Quora Visit the source

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For anybody coming across this topic, now here is a computer vision specific ' addon' on top of Storm called StormCV on github (https://github.com/sensorstorm/StormCV).  "The platform enables the development of distributed video processing pipelines which can be deployed on Storm clusters."

Anonymous

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