3D OBJECT ACQUISITION SYSTEM

This paper present the study on the investigation of the procedures to obtain 3 dimension (3D) acquisition system. The processes start by determining the best pattern to be used in obtaining the best deformation pattern image. Three pattern being projected on the the test object to see the pattern deformation. Pattern which give clear and vivid image when capture by the camera will be selected. Vivid deformation pattern will be used for further analyze by using the software. For software related, the deformation pattern that being choose to analyze will give the data coordinates of the test object. Based on the data obtained, the 3D system of the test data can be acquire. With the data coordinates also, polynomial equation algorithm can be generated to acquire the polynomial equation related with pixel coordinates depth corresponding with the real world depth. This paper will present the investigation in choosing the best projected pattern to be implemented in obtaining the 3D system as well as the image acquisition and analysis using MATLAB to produce desired equatio

Multi-camera Realtime 3D Tracking of Multiple Flying Animals

Automated tracking of animal movement allows analyses that would not otherwise be possible by providing great quantities of data. The additional capability of tracking in realtime - with minimal latency - opens up the experimental possibility of manipulating sensory feedback, thus allowing detailed explorations of the neural basis for control of behavior. Here we describe a new system capable of tracking the position and body orientation of animals such as flies and birds. The system operates with less than 40 msec latency and can track multiple animals simultaneously. To achieve these results, a multi target tracking algorithm was developed based on the Extended Kalman Filter and the Nearest Neighbor Standard Filter data association algorithm. In one implementation, an eleven camera system is capable of tracking three flies simultaneously at 60 frames per second using a gigabit network of nine standard Intel Pentium 4 and Core 2 Duo computers. This manuscript presents the rationale and details of the algorithms employed and shows three implementations of the system. An experiment was performed using the tracking system to measure the effect of visual contrast on the flight speed of Drosophila melanogaster. At low contrasts, speed is more variable and faster on average than at high contrasts. Thus, the system is already a useful tool to study the neurobiology and behavior of freely flying animals. If combined with other techniques, such as `virtual reality'-type computer graphics or genetic manipulation, the tracking system would offer a powerful new way to investigate the biology of flying animals.Comment: pdfTeX using libpoppler 3.141592-1.40.3-2.2 (Web2C 7.5.6), 18 pages with 9 figure

Flexible registration method for light-stripe sensors considering sensor misalignments

In many application areas such as object reconstruction or quality assurance, it is required to completely or partly measure the shape of an object or at least the cross section of the required object region. For complex geometries, therefore, multiple views are needed to bypass undercuts respectively occlusions. Hence, a multi-sensor measuring system for complex geometries has to consist of multiple light-stripe sensors that are surrounding the measuring object in order to complete the measurements in a prescribed time. The number of sensors depends on the object geometry and dimensions. In order to create a uniform 3D data set from the data of individual sensors, a registration of each individual data set into a common global coordinate system has to be performed. Stateof- the-art registration methods for light-stripe sensors use only data from object intersection with the respective laser plane of each sensor. At the same time the assumption is met that all laser planes are coplanar and that there are corresponding points in two data sets. However, this assumption does not represent the real case, because it is nearly impossible to align multiple laser planes in the same plane. For this reason, sensor misalignments are neglected by this assumption. In this work a new registration method for light-stripe sensors is presented that considers sensor misalignments as well as intended sensor displacements and tiltings. The developed method combines 3D pose estimation and triangulated data to properly register the real sensor pose in 3D space. © 2017 SPIE

View generated database

This document represents the final report for the View Generated Database (VGD) project, NAS7-1066. It documents the work done on the project up to the point at which all project work was terminated due to lack of project funds. The VGD was to provide the capability to accurately represent any real-world object or scene as a computer model. Such models include both an accurate spatial/geometric representation of surfaces of the object or scene, as well as any surface detail present on the object. Applications of such models are numerous, including acquisition and maintenance of work models for tele-autonomous systems, generation of accurate 3-D geometric/photometric models for various 3-D vision systems, and graphical models for realistic rendering of 3-D scenes via computer graphics

3D OBJECT ACQUISITION SYSTEM

This paper present the study on the investigation of the procedures to obtain 3 dimension (3D) acquisition system. The processes start by determining the best pattern to be used in obtaining the best deformation pattern image. Three pattern being projected on the the test object to see the pattern deformation. Pattern which give clear and vivid image when capture by the camera will be selected. Vivid deformation pattern will be used for further analyze by using the software. For software related, the deformation pattern that being choose to analyze will give the data coordinates of the test object. Based on the data obtained, the 3D system of the test data can be acquire. With the data coordinates also, polynomial equation algorithm can be generated to acquire the polynomial equation related with pixel coordinates depth corresponding with the real world depth. This paper will present the investigation in choosing the best projected pattern to be implemented in obtaining the 3D system as well as the image acquisition and analysis using MATLAB to produce desired equatio

Multi-camera real-time three-dimensional tracking of multiple flying animals

Automated tracking of animal movement allows analyses that would not otherwise be possible by providing great quantities of data. The additional capability of tracking in real time—with minimal latency—opens up the experimental possibility of manipulating sensory feedback, thus allowing detailed explorations of the neural basis for control of behaviour. Here, we describe a system capable of tracking the three-dimensional position and body orientation of animals such as flies and birds. The system operates with less than 40 ms latency and can track multiple animals simultaneously. To achieve these results, a multi-target tracking algorithm was developed based on the extended Kalman filter and the nearest neighbour standard filter data association algorithm. In one implementation, an 11-camera system is capable of tracking three flies simultaneously at 60 frames per second using a gigabit network of nine standard Intel Pentium 4 and Core 2 Duo computers. This manuscript presents the rationale and details of the algorithms employed and shows three implementations of the system. An experiment was performed using the tracking system to measure the effect of visual contrast on the flight speed of Drosophila melanogaster. At low contrasts, speed is more variable and faster on average than at high contrasts. Thus, the system is already a useful tool to study the neurobiology and behaviour of freely flying animals. If combined with other techniques, such as ‘virtual reality’-type computer graphics or genetic manipulation, the tracking system would offer a powerful new way to investigate the biology of flying animals