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Accession Number ADA584774
Title High Scalability Video ISR Exploitation.
Publication Date Oct 2012
Media Count 17p
Personal Author D. Donavanik M. Czajkowski
Abstract The Intelligence Community uses computer vision (CV) algorithms on data from state-of-the-art sensors and platforms (e.g. Autonomous Real-Time Ground Ubiquitous Surveillance, ARGUS) on the National Image Interpretability Rating Scale (NIIRS) at level 6. Ultra-high quality cameras like the Digital Cinema 4K (DC-4K), which recognizes objects smaller than people, will be available soon for Wide-Area Motion Intelligence (WAMI). However, even if a platform was equipped with DC-4K, it would useless without CV algorithms to quickly process the vast quantities of data captured. (U) Today, several CV algorithms scale up by partitioning data across multiple nodes of computation. The standard approach is to increase the amount of processing power (e.g. GPUs) available. However, to achieve NIIRS level 7+ an emerging problem must be addressed: hard disk read latency. Reductions in disk read latency have not kept pace with increases in volume from 1990 through today. For example, reading a 3TB full disk from beginning to end takes hours. Considering that a NIIRS-8 DC-4K camera captures 32MB of data per frame, it would capture 3.2TB of data in a single mission hour. Industry has already solved this 'big data' problem in large-scale text processing through cloud computing architectures like Apache Hadoop. Hadoop applies a parallel batchprocessing paradigm that reads data from multiple hard disks simultaneously called Map/Reduce. In contrast to Hadoop, Modern CV algorithms assume a sequential data stream being read in order. While certain computations can be made in parallel already, integrating and correlating features computed simultaneously from randomly accessed portions of the data stream is an unmet challenge.
Keywords Algorithms
Cloud computing
Computer vision
Digital systems
High rate
Motion intelligence
Scene understanding
Video signals
Visual saliency

Source Agency Non Paid ADAS
NTIS Subject Category 72B - Algebra, Analysis, Geometry, & Mathematical Logic
62 - Computers, Control & Information Theory
Corporate Author Lockheed Martin, Cherry Hill, NJ. Advanced Technology Labs.
Document Type Technical report
Title Note Conference paper.
NTIS Issue Number 1403
Contract Number N/A

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