Synthetic Vision System

A synthetic vision system or SVS in general, refers to any system which creates the ability to view optic signals artificially. However, it also has a few highly specific meanings.

1. A synthetic vision system is an aid to situational awareness for pilots. Typically it is a set of data files on terrain elevation and type, wind patterns, and occasionally other aircraft. All three are tuied to a rendering engine which creates on a monitor, a picture of the environment around the plane, in 3D. GPS data is typically added to triangulate position, and the result is a far greater idea of the plane?s position than the pilot?s cockpit view would normally afford.

This is sometimes also known as Pictorial Format Avionics.

See Also: Pictorial Format Avionics, Path-In-The-Sky, Highway In The Sky

2. A second meaning of synthetic vision system is a vision system to remotely pilot UAVs. In this instance, the meaning is the same as above, but the SVS view and an on-board camera, are the only views the pilot sees.

Below, we offer a selection of links from our resource databases which may match this term.

DWL FWL Highway In The Sky HITS

Path In The Sky SVS Synthetic Vision System

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Probing the Differences Between Organic Vision and Machine Vision
A group of researchers from UC Santa Barbara have been comparing the human visual system to machine vision systems from an architectual and programming perspective, to see what, exactly makes human vision systems more efficient - and gain some insight on how to replicate that.

Reverse Engineering The Ability to See
There are a few, albeit exceedingly rare cases, where after a lifetime of blindness, a human's vision is naturally restored. These cases, properly studied, are yielding impressive amounts of data on how a vision system forms in a mature mind - and thus how to recreate the same, in machine vision.

Multiple View Geometry in Computer Vision

A basic problem in computer vision is to understand the structure of a physical sceene from just one or two camera?s perspective. This book attempts to provide a basic background in everything you need to know to be able to create a computer vision system, and train it to deal with the physical world.

Designing Virtual Reality Systems: The Structured Approach

This book is very much a holistic first-timer?s guide to creating a hideously complex system ? a full virtual reality. The book describes a VR system as ?a system that provides a synthetic experience for its user(s)?, a definition which could not possibly be any broader.

Cells with double vision
Unlike in the peripheral nervous system, where cells are often unable to distinguish which branching pathway an electrical system is travelling from, the central nervous system makes use of sophisticated internal networks not too dissimilar from an IP record, to differentiate between nervous pathways.

Optical Machine Vision Navigation System Found in Flies
A study conducted to understand how flies and bees can navigate so precisely using just natural sunlight, has interesting implications for machine vision, and adding additional sense-based navigation systems to UAVs and UGVs without adding the weight or cost of any extra hardware.

Dark City: A Dystopian Synthetic World
Plotline Review of the film Dark City, a dystopian synthetic reality storyline which questions deeply the nature of self, and of reality.

An Invitation to 3-D Vision

This book gives senior undergraduate and beginning graduate students and researchers in computer vision, applied mathematics, computer graphics, and robotics a self-contained introduction to the geometry of 3D vision; that is the reconstruction of 3D models of objects from a collection of 2D images.

Improving LIDAR: Calibrate and Scan
A new technology currently being trialled by the EU, seeks to substantially improve the LIDAR machine vision system's accuracy. To enable the system to differentiate between moving and stationary targets, and prioritise where to scan.

Introductory Techniques for 3-D Computer Vision

An applied introduction to modern computer vision, focusing on a set of computational techniques for 3-D imaging. Covers a wide range of fundamental problems encountered within computer vision and provides detailed algorithmic and theoretical solutions for each. Each chapter concentrates on a specific problem and solves it by building on previous results.

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