6 research outputs found
Reality Computing: An end-to-end process for Herpetological Heritage
Documentation of institutional biological collections are essential for scientific studies and conservation of the biodiversity of a region. In particular, preserved specimens require the development of a short- and long-term plan to prevent damage.
In this context, the 3D digitisation of this type of documentation provides innovative mechanisms to safeguard the valuable information provided by the collections and at the same time prevent any possible loss of information. At the moment, the potential of laser scanning in model reconstruction is well-known, but developed works using this method for 3D construction reveal a lack of reliable, precise and flexible solutions.
Furthermore, visualisation of results is often very useless and does not go beyond web-based applications.
This work presents an analysis of 3D modelling using two digitisation techniques: laser scanning and photogrammetry; combined with real time VR and AR visualizations and 3D printing.XVI Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI
Reality Computing: An end-to-end process for Herpetological Heritage
Documentation of institutional biological collections are essential for scientific studies and conservation of the biodiversity of a region. In particular, preserved specimens require the development of a short- and long-term plan to prevent damage.
In this context, the 3D digitisation of this type of documentation provides innovative mechanisms to safeguard the valuable information provided by the collections and at the same time prevent any possible loss of information. At the moment, the potential of laser scanning in model reconstruction is well-known, but developed works using this method for 3D construction reveal a lack of reliable, precise and flexible solutions.
Furthermore, visualisation of results is often very useless and does not go beyond web-based applications.
This work presents an analysis of 3D modelling using two digitisation techniques: laser scanning and photogrammetry; combined with real time VR and AR visualizations and 3D printing.XVI Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI
Cyclododecane as opcifier for digitalization of archaeological glass
[EN] This paper faces the problem of acquiring archaeological artifacts using triangulation based 3D laser
scanners and focusing on reflective/refractive surfaces. This kind of artifacts are mostly made of glass
or polished metal, and the properties of their surfaces violate most of the fundamental assumptions
made by vision algorithms. Also, the unique and fragile nature of archaeological artifacts adds an extra
constraint to the acquisition process: the use of industrial whitening sprays has to be avoided, due to
the physicochemical processes required to clean the surface after scanning and because the chemical
properties of these sprays may damage the original object. As an alternative to them, a new way to use
a common conservation material is proposed: the use of cyclododecane as a whitening spray. Thanks to
its chemical stability and to the fact that it sublimes at room temperature, together with its good filmforming
capabilities, a set of evaluation tests is presented to prove thatthe error introduced by the opaque
thin layer created on the surface of the artifact is smaller than the accuracy of the 3D scanner and, thus,
no acquisition errors are introduced. A comparison with general-purpose industrial whitening sprays is
also presented, and achieved results show no significant differences in the quality of the resulting 3D
models.This work is supported by the "Programa de Ayudas de Investigacion y Desarrollo (PAID)" of the Universitat Politecnica de Valencia and the "Plan Nacional de I+D+i 2008-2011" from the Ministerio de Economia y Competitividad of Spain, Projects ID: HAR2012-38391-C02-01 and HAR2012-38391-C02-02.Díaz Marín, MDC.; Aura Castro, E.; Sánchez Belenguer, C.; Vendrell Vidal, E. (2016). Cyclododecane as opcifier for digitalization of archaeological glass. Journal of Cultural Heritage. 17:131-140. https://doi.org/10.1016/j.culher.2015.06.003S1311401
Reality Computing: An end-to-end process for Herpetological Heritage
Documentation of institutional biological collections are essential for scientific studies and conservation of the biodiversity of a region. In particular, preserved specimens require the development of a short- and long-term plan to prevent damage.
In this context, the 3D digitisation of this type of documentation provides innovative mechanisms to safeguard the valuable information provided by the collections and at the same time prevent any possible loss of information. At the moment, the potential of laser scanning in model reconstruction is well-known, but developed works using this method for 3D construction reveal a lack of reliable, precise and flexible solutions.
Furthermore, visualisation of results is often very useless and does not go beyond web-based applications.
This work presents an analysis of 3D modelling using two digitisation techniques: laser scanning and photogrammetry; combined with real time VR and AR visualizations and 3D printing.XVI Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI
Image processing and analysis : applications and trends
The computational analysis of images is challenging as it usually involves tasks such as segmentation, extraction of representative features, matching, alignment, tracking, motion analysis, deformation estimation, and 3D reconstruction. To carry out each of these tasks in a fully automatic, efficient and robust manner is generally demanding.The quality of the input images plays a crucial role in the success of any image analysis task. The higher their quality, the easier and simpler the tasks are. Hence, suitable methods of image processing such as noise removal, geometric correction, edges and contrast enhancement or illumination correction are required.Despite the challenges, computational methods of image processing and analysis are suitable for a wide range of applications.In this paper, the methods that we have developed for processing and analyzing objects in images are introduced. Furthermore, their use in applications from medicine and biomechanics to engineering and materials sciences are presented
Intelligent sensing for robot mapping and simultaneous human localization and activity recognition
Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2011.Thesis (Ph. D.) -- Bilkent University, 2011.Includes bibliographical references leaves 147-163.We consider three different problems in two different sensing domains, namely
ultrasonic sensing and inertial sensing. Since the applications considered in each
domain are inherently different, this thesis is composed of two main parts. The
approach common to the two parts is that raw data acquired from simple sensors
is processed intelligently to extract useful information about the environment.
In the first part, we employ active snake contours and Kohonen’s selforganizing
feature maps (SOMs) for representing and evaluating discrete point
maps of indoor environments efficiently and compactly. We develop a generic
error criterion for comparing two different sets of points based on the Euclidean
distance measure. The point sets can be chosen as (i) two different sets of map
points acquired with different mapping techniques or different sensing modalities,
(ii) two sets of fitted curve points to maps extracted by different mapping techniques
or sensing modalities, or (iii) a set of extracted map points and a set of
fitted curve points. The error criterion makes it possible to compare the accuracy
of maps obtained with different techniques among themselves, as well as with an
absolute reference. We optimize the parameters of active snake contours and
SOMs using uniform sampling of the parameter space and particle swarm optimization.
A demonstrative example from ultrasonic mapping is given based on
experimental data and compared with a very accurate laser map, considered an
absolute reference. Both techniques can fill the erroneous gaps in discrete point
maps. Snake curve fitting results in more accurate maps than SOMs because it is
more robust to outliers. The two methods and the error criterion are sufficiently
general that they can also be applied to discrete point maps acquired with other
mapping techniques and other sensing modalities.
In the second part, we use body-worn inertial/magnetic sensor units for recognition
of daily and sports activities, as well as for human localization in GPSdenied
environments. Each sensor unit comprises a tri-axial gyroscope, a tri-axial
accelerometer, and a tri-axial magnetometer. The error characteristics of the sensors
are modeled using the Allan variance technique, and the parameters of lowand
high-frequency error components are estimated.
Then, we provide a comparative study on the different techniques of classifying
human activities that are performed using body-worn miniature inertial and
magnetic sensors. Human activities are classified using five sensor units worn
on the chest, the arms, and the legs. We compute a large number of features
extracted from the sensor data, and reduce these features using both Principal
Components Analysis (PCA) and sequential forward feature selection (SFFS).
We consider eight different pattern recognition techniques and provide a comparison
in terms of the correct classification rates, computational costs, and their
training and storage requirements. Results with sensors mounted on various locations
on the body are also provided. The results indicate that if the system
is trained by the data of an individual person, it is possible to obtain over 99%
correct classification rates with a simple quadratic classifier such as the Bayesian
decision method. However, if the training data of that person are not available
beforehand, one has to resort to more complex classifiers with an expected correct
classification rate of about 85%.
We also consider the human localization problem using body-worn inertial/
magnetic sensors. Inertial sensors are characterized by drift error caused
by the integration of their rate output to get position information. Because of
this drift, the position and orientation data obtained from inertial sensor signals
are reliable over only short periods of time. Therefore, position updates from externally
referenced sensors are essential. However, if the map of the environment
is known, the activity context of the user provides information about position. In
particular, the switches in the activity context correspond to discrete locations
on the map. By performing activity recognition simultaneously with localization,
one can detect the activity context switches and use the corresponding position
information as position updates in the localization filter. The localization filter
also involves a smoother, which combines the two estimates obtained by running
the zero-velocity update (ZUPT) algorithm both forward and backward in time.
We performed experiments with eight subjects in an indoor and an outdoor environment
involving “walking,” “turning,” and “standing” activities. Using the
error criterion in the first part of the thesis, we show that the position errors can
be decreased by about 85% on the average. We also present the results of a 3-D
experiment performed in a realistic indoor environment and demonstrate that it
is possible to achieve over 90% error reduction in position by performing activity
recognition simultaneously with localization.Altun, KeremPh.D