SBIR/STTR Research Award

Cognitive Processing and Exploitation of 3D Laser Imaging Detection and Ranging (LIDAR) Imagery Data

Award identifier fab3e06b6268525361ca2f833498903275b52735577fb767fbab1767bab98712Awarding agency Department of Defense · Air Force

Award amount

$150,000

Program and phase

SBIR · Phase I

Award year

2016

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
TOYON RESEARCH CORPORATION
Proposal award date
2016-06-03
Contract end date
2017-03-03
UEI
PK1CB3L39XX8
Solicitation number
2016.1
Topic code
AF161-138

Research abstract

ABSTRACT: Toyon Research Corp. proposes to develop innovative cognitive processing algorithms to perform ultra-fast identification and classification (uFIC) of structural information directly from 3-dim LiDAR point-cloud data. The proposed algorithms are based on a model of human cognition, which involves coarsely processing data to identify regions of interest (ROI), and subsequently increasing the granularity of detection to resolve objects and patterns. Like the human visual cortex, our algorithmic cortex is composed of several layers, which filter and interpret local point-data correlations at different scales using simple geometric models. Multi-scale point and group associations are stored in efficient membership structures, which are built at each layer and refined with low complexity updates. The resulting system is highly tunable, via a number of objective- function parameters, and adaptable to various object geometries and signal modalities. Furthermore, the system is capable of real-time performance, with immediate extensions employing massively parallel GPU and distributed CPU architectures such as OpenMPI.; BENEFIT: The tool will provide an intuitive user interface for visualizing, searching, and annotating 3-dim LiDAR datasets in real-time. The prototype will be based on a geographic information system (GIS) framework with a graphical user interface, 3D environment models, terrain and overlay visualizations, import/export of standard data formats, and accompanying CAD tool to generate synthetic models for training. The recognition algorithms will consist of low-level geometry extraction codes coupled with a trainable software stack (modeled on human neural anatomy and deep learning architectures) that can exploit training data. The resulting tool will enable an analyst to load up a point-cloud file, automatically find geometric objects from a training set, and visualize them using in a scene using simple shading and wireframe models.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

601 SBIR/STTR records share this UEI (1986–2026). Reported award amounts total $249,287,075. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, Department of Commerce, Department of Homeland Security, National Aeronautics and Space Administration, Department of Transportation, Department of Energy

Contractor profile

TOYON RESEARCH CORPORATION

Historical federal award activity, when published, is on that contractor profile. Matched by UEI only.

Agency intelligence

Department of Defense

NAICS intelligence

This classification comes from the contractor profile, not from the SBIR award record.

Contractor industry classification NAICS 541512

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