Horizon extraction in an optical collision avoidance sensor

Minwalla, Cyrus; Watters, Kyle; Thomas, Paul J.; Hornsey, Richard; Ellis, Kris; Jennings, Sion

doi:10.1109/ccece.2011.6030440

Cited by 3 publications

(4 citation statements)

References 10 publications

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“…Without an obvious boundary, image processing techniques may be influenced by scene structure and cloud cover to detect a false horizon contour, and are not considered as reliable as a theoretical horizon computed from the platform INS measurements. Previous efforts based on machine learning techniques extracted the contour defined by the groundhorizon boundary [Minwalla et al, 2011]. Such a contour can reveal geological and man-made topological features that a theoretical horizon will not capture, and may prove useful when flying at low altitudes in a city or near rocky terrain.…”

Section: Inertial Reference Horizonmentioning

confidence: 99%

Why the Horizon Is Important for Airborne Sense and Avoid Applications

Minwalla

Ellis

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The utility of the horizon for airborne sense-and-avoid (ABSAA) applications is explored in this work. The horizon is a feature boundary across which an airborne scene can be separated into surface and sky and serves as a salient, heading-independent feature that may be mapped into an electro-optical sensor. The virtual horizon as established in this paper represents the horizon that would be seen assuming a featureless earth model and infinite visibility and is distinct from the apparent horizon in an imaging sensor or the pilot's eye. For level flight, non-maneuvering collision course trajectories, it is expected that targets of interest will appear in close proximity to this virtual horizon. This paper presents a model for establishing the virtual horizon and its projection into a camera reference plane as part of the sensing element in an ABSAA system. Evaluation of the model was performed on a benchmark dataset of airborne collision geometries flown at the National Research Council (NRC) using the Cerberus camera array. The model was compared against ground truth flight test data collected using high accuracy inertial navigation systems aboard aircraft on several 'near-miss' intercepts. The paper establishes the concept of 'virtual horizon proximity' (VHP), the minimum distance from a detected target and the virtual horizon, and investigates the utility of using this metric as a means of rejecting false positive detections, and increasing range at first detection through the use of a region of interest (ROI) mask centred on the virtual horizon. The use of this horizon-centred ROI was shown to increase the range at first detection by an average factor of two, and was shown to reduce false positives for six popular feature detector algorithms applied across the suite of flight test imagery.

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Section: Inertial Reference Horizonmentioning

confidence: 99%

Why the Horizon Is Important for Airborne Sense and Avoid Applications

Minwalla

Ellis

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Specific to the planetary surface navigation are the unknown terrain features as seen from the rover/lander camera orientation and resolution. This makes classification based methods ( [3], [7], [8], [9], [10]) difficult to use. A direct color based sky segmentation is also unreliable for images captured in various missions.…”

Section: Introductionmentioning

confidence: 99%

Horizon based orientation estimation for planetary surface navigation

Bouyssounouse

Nefian

Thomas

et al. 2016

2016 IEEE International Conference on Image Processing (ICIP)

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Planetary rovers navigate in extreme environments for which a Global Positioning System (GPS) is unavailable, maps are restricted to relatively low resolution provided by orbital imagery, and compass information is often lacking due to weak or not existent magnetic fields. However, an accurate rover localization is particularly important to achieve the mission success by reaching the science targets, avoiding negative obstacles visible only in orbital maps, and maintaining good communication connections with ground. This paper describes a horizon solution for precise rover orientation estimation. The detected horizon in imagery provided by the on board navigation cameras is matched with the horizon rendered over the existing terrain model. The set of rotation parameters (roll, pitch yaw) that minimize the cost function between the two horizon curves corresponds to the rover estimated pose.

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“…In contrast to the approach which focuses on finding only the horizon boundary, methods which classify all pixels as belonging to either sky or ground can also be found [26], [28], [30], [31], [32], [34], [35]. These approaches don't make any simplifying assumptions on flight altitude or hori zon shape.…”

Section: Introductionmentioning

confidence: 99%

“…[31]. Classification of pixels typically breaks down to either using pixelintensities for features or a number of statistics computed around a neighborhood o f each pixel or a combination of both.…”

mentioning

confidence: 99%

Convolutional neural network-based vision systems for unmanned aerial vehicles

Verbickas¹

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Horizon extraction in an optical collision avoidance sensor

Cited by 3 publications

References 10 publications

Why the Horizon Is Important for Airborne Sense and Avoid Applications

Why the Horizon Is Important for Airborne Sense and Avoid Applications

Horizon based orientation estimation for planetary surface navigation

Convolutional neural network-based vision systems for unmanned aerial vehicles

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