A1designer a2 a20 a-24 a2c-net112 a2c-net113 a2c-net114 a2c-net115 a2c-net116 a2c-net117 a2c-net122 a2c-net231 a2c-net232 a2c-net233 a2c-net234. Dtdg777 dtdvsa dtdvsb dtdvsc dtdvsd dtdvse dtedi dtel dtenggara dtfg dtgripaa dth dthomas dthompso dthompson dti dtit dtix dtl dtle dtm dtm1 dtmmr dtmo dtmt.

NIKON DTM-A20LG TOTAL STATION • 30x telescope with world-famous Nikon ED coated optics• 10' minimum display/10' accuracy• 7,400 foot range to triple prism• Dual LCD displays/full keypads• Vertical compensation• Lumi-Guide tracking light facilitates prism setup• REM, RDM, coordinate computation, stake out, and more• Standard RS-232C data interface• Easy operation The DTM-A20LG is a rugged and easy to use total station first introduced in 1991, and which continues to remain popular to this day. While lacking on-board data collection, you'll still find many of the essential features common to more recent models. This unit has seen its share of use, and is cosmetically in fair condition with wear marks from handling; the operating condition is in all regards, however, excellent, having been completely serviced and calibrated in our shop. It comes with the hard case, charger, 2 (good) batteries, and a (photo) copy of the owners manual. The case looks well used also, but is 100% sound and secure. Ready to go to work for just.SOLD!! Please don't hesitate to or call (562-426-1306) with your questions.

Visitors from autolevel.com and elsewhere are encouraged to click to view more great used equipment from Mohave!

• Edwards, Thomas R. 1997-02-01 Forensic video image analysis is a new scientific tool for perpetrator enhancement and identification in poorly recorded crime scene situations. Forensic video image analysis is emerging technology for law enforcement, industrial security and surveillance addressing the following problems often found in these poor quality video recorded incidences. • Sadlier, D.

A.; O'Connor, N. 2010-04-01 This paper details and evaluates a system that aims to provide continuous robust localisation ('tracking') of vehicles throughout the scenes of aerial video footage captured by Unmanned Aerial Vehicles ( UAVs). The scientific field of UAV object tracking is well studied in the field of computer vision, with a variety of solutions offered. However, rigorous evaluation is infrequent, and further novelty lies here in our exploration of the benefits of combined modality processing, in conjunction with a proposed adaptive feature weighting technique. Building on our previously reported framework for object-tracking in multi-spectral video1, moving vehicles are initially located by exploiting their intrascene displacement within a camera-motion compensated video-image domain. For each detected vehicle, a spatiogram2-based representation is then extracted, which is a representative form that aims to bridge the gap between the 'coarseness' of histograms and the 'rigidity' of pixel templates. Spatiogram-based region matching then ensues for each vehicle, towards determining their new locations throughout the subsequent frames of the video sequence.

The framework is flexible in that, in addition to the exploitation of traditional visible spectrum features, it can accommodate the inclusion of additional feature sources, demonstrated here via the attachment of an infrared channel. Furthermore, the system provides the option of enabling an adaptive feature weighting mechanism, whereby the transient ability of certain features to occasionally outperform others is exploited in an adaptive manner, to the envisaged benefit of increased tracking robustness.

The system was developed and tested using the DARPA VIVID2 video dataset3, which is a suite of multi-spectral (visible and thermal infrared) video files captured from an airborne platform flying at various altitudes. Evaluation of the system is quantitative, which differentiates it from a large portion of the existing literature • Colla, Simone; Manesis, Charalampos 2013-08-01 The current paper focuses on the capture, fusion and process of aerial imagery in order to leverage full motion video, giving analysts the ability to collect, analyze, and maximize the value of video assets. Unmanned aerial vehicles ( UAV) have provided critical real-time surveillance and operational support to military organizations, and are a key source of intelligence, particularly when integrated with other geospatial data. In the current workflow, at first, the UAV operators plan the flight by using a flight planning software. During the flight the UAV send a live video stream directly on the field to be processed by Intergraph software, to generate and disseminate georeferenced images trough a service oriented architecture based on ERDAS Apollo suite. The raw video-based data sources provide the most recent view of a situation and can augment other forms of geospatial intelligence - such as satellite imagery and aerial photos - to provide a richer, more detailed view of the area of interest.

To effectively use video as a source of intelligence, however, the analyst needs to seamlessly fuse the video with these other types of intelligence, such as map features and annotations. Intergraph has developed an application that automatically generates mosaicked georeferenced image, tags along the video route which can then be seamlessly integrated with other forms of static data, such as aerial photos, satellite imagery, or geospatial layers and features. Consumers will finally have the ability to use a single, streamlined system to complete the entire geospatial information lifecycle: capturing geospatial data using sensor technology; processing vector, raster, terrain data into actionable information; managing, fusing, and sharing geospatial data and video toghether; and finally, rapidly and securely delivering integrated information products, ensuring individuals can make timely decisions.

• Hosseinpoor, H. R.; Samadzadegan, F.; Dadras Javan, F. 2015-12-01 There are an increasingly large number of uses for Unmanned Aerial Vehicles ( UAVs) from surveillance, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters.

This low accuracy which implicates that it cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using a linear Kalman filter, which provides a smoothed estimate of target location and target velocity.

The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors and Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process. • Gerald, II, Rex E.; Sanchez, Jairo; Rathke, Jerome W.

2004-08-10 A video toroid cavity imager for in situ measurement of electrochemical properties of an electrolytic material sample includes a cylindrical toroid cavity resonator containing the sample and employs NMR and video imaging for providing high-resolution spectral and visual information of molecular characteristics of the sample on a real-time basis. A large magnetic field is applied to the sample under controlled temperature and pressure conditions to simultaneously provide NMR spectroscopy and video imaging capabilities for investigating electrochemical transformations of materials or the evolution of long-range molecular aggregation during cooling of hydrocarbon melts. The video toroid cavity imager includes a miniature commercial video camera with an adjustable lens, a modified compression coin cell imager with a fiat circular principal detector element, and a sample mounted on a transparent circular glass disk, and provides NMR information as well as a video image of a sample, such as a polymer film, with micrometer resolution.

• Christensen, Wynn; Anderson, Forrest L.; Kortegaard, Birchard L. 1991-01-01 An optical beam position controller in which a video camera captures an image of the beam in its video frames, and conveys those images to a processing board which calculates the centroid coordinates for the image.

The image coordinates are used by motor controllers and stepper motors to position the beam in a predetermined alignment. In one embodiment, system noise, used in conjunction with Bernoulli trials, yields higher resolution centroid coordinates. • Xiang, Ren; Sun, Min; Jiang, Cheng; Liu, Lei; Zheng, Hui; Li, Xiaodong 2014-11-01 With the development of UAV technology, UAVs are used widely in multiple fields such as agriculture, forest protection, mineral exploration, natural disaster management and surveillances of public security events. In contrast of traditional manned aerial remote sensing platforms, UAVs are cheaper and more flexible to use.

So users can obtain massive image data with UAVs, but this requires a lot of time to process the image data, for example, Pix4 UAV need approximately 10 hours to process 1000 images in a high performance PC. But disaster management and many other fields require quick respond which is hard to realize with massive image data. Aiming at improving the disadvantage of high time consumption and manual interaction, in this article a solution of fast UAV image stitching is raised. GPS and POS data are used to pre-process the original images from UAV, belts and relation between belts and images are recognized automatically by the program, in the same time useless images are picked out. This can boost the progress of finding match points between images.

Levenberg-Marquard algorithm is improved so that parallel computing can be applied to shorten the time of global optimization notably. Besides traditional mosaic result, it can also generate superoverlay result for Google Earth, which can provide a fast and easy way to show the result data. In order to verify the feasibility of this method, a fast mosaic system of massive UAV images is developed, which is fully automated and no manual interaction is needed after original images and GPS data are provided.

A test using 800 images of Kelan River in Xinjiang Province shows that this system can reduce 35%-50% time consumption in contrast of traditional methods, and increases respond speed of UAV image processing rapidly. • Sieberth, Till; Wackrow, Rene; Chandler, Jim H.

2016-12-01 Unmanned aerial vehicles ( UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by an UAV, which have a high ground resolution and good spectral and radiometrical resolution, due to the low flight altitudes combined with a high resolution camera. UAV image flights are also cost effective and have become attractive for many applications including, change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs.

This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms. The detection and removal of these images is currently achieved manually, which is both time consuming and prone to error, particularly for large image-sets. To increase the quality of data processing an automated process is necessary, which must be both reliable and quick. This paper describes the development of an automatic filtering process, which is based upon the quantification of blur in an image. Images with known blur are processed digitally to determine a quantifiable measure of image blur. The algorithm is required to process UAV images fast and reliably to relieve the operator from detecting blurred images manually. The newly developed method makes it possible to detect blur caused by linear camera displacement and is based on human detection of blur.

Humans detect blurred images best by comparing it to other images in order to establish whether an image is blurred or not. The developed algorithm simulates this procedure by creating an image for comparison using image processing. Creating internally a comparable image makes the method independent of • Se, Stephen; Nadeau, Christian; Wood, Scott 2011-05-01 Airborne surveillance and reconnaissance are essential for successful military missions. Such capabilities are critical for troop protection, situational awareness, mission planning, damage assessment, and others. Unmanned Aerial Vehicles ( UAVs) gather huge amounts of video data but it is extremely labour-intensive for operators to analyze hours and hours of received data. At MDA, we have developed a suite of tools that can process the UAV video data automatically, including mosaicking, change detection and 3D reconstruction, which have been integrated within a standard GIS framework.

In addition, the mosaicking and 3D reconstruction tools have also been integrated in a Service Oriented Architecture (SOA) framework. The Visualization and Exploitation Workstation (VIEW) integrates 2D and 3D visualization, processing, and analysis capabilities developed for UAV video exploitation. Visualization capabilities are supported through a thick-client Graphical User Interface (GUI), which allows visualization of 2D imagery, video, and 3D models. The GUI interacts with the VIEW server, which provides video mosaicking and 3D reconstruction exploitation services through the SOA framework. The SOA framework allows multiple users to perform video exploitation by running a GUI client on the operator's computer and invoking the video exploitation functionalities residing on the server. This allows the exploitation services to be upgraded easily and allows the intensive video processing to run on powerful workstations. MDA provides UAV services to the Canadian and Australian forces in Afghanistan with the Heron, a Medium Altitude Long Endurance (MALE) UAV system.

On-going flight operations service provides important intelligence, surveillance, and reconnaissance information to commanders and front-line soldiers. • 2002-01-01 In this video, astronaut Peggy Whitson uses the Human Research Facility (HRF) Ultrasound Imaging System in the Destiny Laboratory of the International Space Station (ISS) to image her own heart. The Ultrasound Imaging System provides three-dimension image enlargement of the heart and other organs, muscles, and blood vessels. It is capable of high resolution imaging in a wide range of applications, both research and diagnostic, such as Echocardiography (ultrasound of the heart), abdominal, vascular, gynecological, muscle, tendon, and transcranial ultrasound. • 2002-01-01 In this video, astronaut Peggy Whitson uses the Human Research Facility (HRF) Ultrasound Imaging System in the Destiny Laboratory of the International Space Station (ISS) to image her own heart.

The Ultrasound Imaging System provides three-dimension image enlargement of the heart and other organs, muscles, and blood vessels. It is capable of high resolution imaging in a wide range of applications, both research and diagnostic, such as Echocardiography (ultrasound of the heart), abdominal, vascular, gynecological, muscle, tendon, and transcranial ultrasound. • Sieberth, T.; Wackrow, R.; Chandler, J. 2013-08-01 Unmanned aerial vehicles ( UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by an UAV, which have a high ground resolution and good spectral and radiometrical resolution, due to the low flight altitudes combined with a high resolution camera.

UAV image flights are also cost effective and have become attractive for many applications including change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs. This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms.

The detection and removal of these images is currently achieved manually, which is both time consuming and prone to error, particularly for large image-sets. To increase the quality of data processing an automated filtering process is necessary, which must be both reliable and quick. This paper describes the development of an automatic filtering process, which is based upon the quantification of blur in an image. A 'shaking table' was used to create images with known blur during a series of laboratory tests.

This platform can be moved in one direction by a mathematical function controlled by a defined frequency and amplitude. The shaking table was used to displace a Nikon D80 digital SLR camera with a user defined frequency and amplitude. The actual camera displacement was measured accurately and exposures were synchronized, which provided the opportunity to acquire images with a known blur effect. Acquired images were processed digitally to determine a quantifiable measure of image blur, which has been created by the actual shaking table function. Once determined • Hathaway, David H.

(Inventor); Meyer, Paul J. (Inventor) 2002-01-01 A method of stabilizing and registering a video image in multiple video fields of a video sequence provides accurate determination of the image change in magnification, rotation and translation between video fields, so that the video fields may be accurately corrected for these changes in the image in the video sequence.

In a described embodiment, a key area of a key video field is selected which contains an image which it is desired to stabilize in a video sequence. The key area is subdivided into nested pixel blocks and the translation of each of the pixel blocks from the key video field to a new video field is determined as a precursor to determining change in magnification, rotation and translation of the image from the key video field to the new video field. • Hathaway, David H. (Inventor); Meyer, Paul J.

(Inventor) 2003-01-01 A method of stabilizing and registering a video image in multiple video fields of a video sequence provides accurate determination of the image change in magnification, rotation and translation between video fields, so that the video fields may be accurately corrected for these changes in the image in the video sequence. In a described embodiment, a key area of a key video field is selected which contains an image which it is desired to stabilize in a video sequence. The key area is subdivided into nested pixel blocks and the translation of each of the pixel blocks from the key video field to a new video field is determined as a precursor to determining change in magnification, rotation and translation of the image from the key video field to the new video field.

• Hathaway, David H. (Inventor); Meyer, Paul J. (Inventor) 2002-01-01 A method of stabilizing and registering a video image in multiple video fields of a video sequence provides accurate determination of the image change in magnification, rotation and translation between video fields, so that the video fields may be accurately corrected for these changes in the image in the video sequence. In a described embodiment, a key area of a key video field is selected which contains an image which it is desired to stabilize in a video sequence. The key area is subdivided into nested pixel blocks and the translation of each of the pixel blocks from the key video field to a new video field is determined as a precursor to determining change in magnification, rotation and translation of the image from the key video field to the new video field. • 2005-05-01 altitude long endurance UAV. Free Download Material Library 3ds Max 9 Service. Magic Bullet Looks Windows 7 64 Bit Free Download here.

• Proposition of “Over-the-Hill” mini- UAV concepts in the frame of FELIN. This position has notably been acquired thanks.interfaces. Nd conditions, it e fully compliant ity between these the formation of order to meet the ion of imagery to ring during joint ANAGs • Interest in use of unmanned aerial vehicles in science has increased in recent years. It is predicted that they will be a preferred remote sensing platform for applications that inform sustainable rangeland management in the future.

The objective of this study was to determine whether UAV video moni. • Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong 2016-08-19 A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle ( UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications.

Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. • Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong 2016-01-01 A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle ( UAV) images.

As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images.

The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

PMID:27548179 • Hinnrichs, Michele; Hinnrichs, Bradford; McCutchen, Earl 2017-02-01 Pacific Advanced Technology (PAT) has developed an infrared hyperspectral camera, both MWIR and LWIR, small enough to serve as a payload on a miniature unmanned aerial vehicles. The optical system has been integrated into the cold-shield of the sensor enabling the small size and weight of the sensor.

This new and innovative approach to infrared hyperspectral imaging spectrometer uses micro-optics and will be explained in this paper. The micro-optics are made up of an area array of diffractive optical elements where each element is tuned to image a different spectral region on a common focal plane array. The lenslet array is embedded in the cold-shield of the sensor and actuated with a miniature piezo-electric motor. This approach enables rapid infrared spectral imaging with multiple spectral images collected and processed simultaneously each frame of the camera.

This paper will present our optical mechanical design approach which results in an infrared hyper-spectral imaging system that is small enough for a payload on a mini- UAV or commercial quadcopter. Also, an example of how this technology can easily be used to quantify a hydrocarbon gas leak's volume and mass flowrates. The diffractive optical elements used in the lenslet array are blazed gratings where each lenslet is tuned for a different spectral bandpass. The lenslets are configured in an area array placed a few millimeters above the focal plane and embedded in the cold-shield to reduce the background signal normally associated with the optics. We have developed various systems using a different number of lenslets in the area array. Depending on the size of the focal plane and the diameter of the lenslet array will determine the spatial resolution.

A 2 x 2 lenslet array will image four different spectral images of the scene each frame and when coupled with a 512 x 512 focal plane array will give spatial resolution of 256 x 256 pixel each spectral image. Another system that we developed uses a 4 x 4.