8,468 research outputs found
A Synergistic Approach for Recovering Occlusion-Free Textured 3D Maps of Urban Facades from Heterogeneous Cartographic Data
In this paper we present a practical approach for generating an
occlusion-free textured 3D map of urban facades by the synergistic use of
terrestrial images, 3D point clouds and area-based information. Particularly in
dense urban environments, the high presence of urban objects in front of the
facades causes significant difficulties for several stages in computational
building modeling. Major challenges lie on the one hand in extracting complete
3D facade quadrilateral delimitations and on the other hand in generating
occlusion-free facade textures. For these reasons, we describe a
straightforward approach for completing and recovering facade geometry and
textures by exploiting the data complementarity of terrestrial multi-source
imagery and area-based information
EgoFace: Egocentric Face Performance Capture and Videorealistic Reenactment
Face performance capture and reenactment techniques use multiple cameras and sensors, positioned at a distance from the face or mounted on heavy wearable devices. This limits their applications in mobile and outdoor environments. We present EgoFace, a radically new lightweight setup for face performance capture and front-view videorealistic reenactment using a single egocentric RGB camera. Our lightweight setup allows operations in uncontrolled environments, and lends itself to telepresence applications such as video-conferencing from dynamic environments. The input image is projected into a low dimensional latent space of the facial expression parameters. Through careful adversarial training of the parameter-space synthetic rendering, a videorealistic animation is produced. Our problem is challenging as the human visual system is sensitive to the smallest face irregularities that could occur in the final results. This sensitivity is even stronger for video results. Our solution is trained in a pre-processing stage, through a supervised manner without manual annotations. EgoFace captures a wide variety of facial expressions, including mouth movements and asymmetrical expressions. It works under varying illuminations, background, movements, handles people from different ethnicities and can operate in real time
Piano Crossing - Walking on a Keyboard
Piano Crossing is an interactive art installation which turns a pedestrian crossing marked with white stripes into a piano keyboard so that pedestrians can generate music by walking over it. Matching tones are generated when a pedestrian is over a particular stripe or key. A digital camera is directed at the crossing from above. A special computer vision application was developed that maps the stripes of the pedestrian crossing to piano keys and which detects over which key is the center of gravity of every pedestrian in the image at any given moment. Special black stripes are added to the crossing, which represent also the black piano keys. The application consists of two parts: (1) initialization, where the model of the abstract piano keyboard is mapped to the image of the pedestrian crossing and (2) the detection of pedestrians on the crossing so that musical tones can be generated according to their locations. The art installation Piano crossing was presented to the public for the first time during the 51st Jazz Festival in Ljubljana in July 2010
Overcoming the Challenges Associated with Image-based Mapping of Small Bodies in Preparation for the OSIRIS-REx Mission to (101955) Bennu
The OSIRIS-REx Asteroid Sample Return Mission is the third mission in NASA's
New Frontiers Program and is the first U.S. mission to return samples from an
asteroid to Earth. The most important decision ahead of the OSIRIS-REx team is
the selection of a prime sample-site on the surface of asteroid (101955) Bennu.
Mission success hinges on identifying a site that is safe and has regolith that
can readily be ingested by the spacecraft's sampling mechanism. To inform this
mission-critical decision, the surface of Bennu is mapped using the OSIRIS-REx
Camera Suite and the images are used to develop several foundational data
products. Acquiring the necessary inputs to these data products requires
observational strategies that are defined specifically to overcome the
challenges associated with mapping a small irregular body. We present these
strategies in the context of assessing candidate sample-sites at Bennu
according to a framework of decisions regarding the relative safety,
sampleability, and scientific value across the asteroid's surface. To create
data products that aid these assessments, we describe the best practices
developed by the OSIRIS-REx team for image-based mapping of irregular small
bodies. We emphasize the importance of using 3D shape models and the ability to
work in body-fixed rectangular coordinates when dealing with planetary surfaces
that cannot be uniquely addressed by body-fixed latitude and longitude.Comment: 31 pages, 10 figures, 2 table
Structured Sparsity Models for Multiparty Speech Recovery from Reverberant Recordings
We tackle the multi-party speech recovery problem through modeling the
acoustic of the reverberant chambers. Our approach exploits structured sparsity
models to perform room modeling and speech recovery. We propose a scheme for
characterizing the room acoustic from the unknown competing speech sources
relying on localization of the early images of the speakers by sparse
approximation of the spatial spectra of the virtual sources in a free-space
model. The images are then clustered exploiting the low-rank structure of the
spectro-temporal components belonging to each source. This enables us to
identify the early support of the room impulse response function and its unique
map to the room geometry. To further tackle the ambiguity of the reflection
ratios, we propose a novel formulation of the reverberation model and estimate
the absorption coefficients through a convex optimization exploiting joint
sparsity model formulated upon spatio-spectral sparsity of concurrent speech
representation. The acoustic parameters are then incorporated for separating
individual speech signals through either structured sparse recovery or inverse
filtering the acoustic channels. The experiments conducted on real data
recordings demonstrate the effectiveness of the proposed approach for
multi-party speech recovery and recognition.Comment: 31 page
Area Estimation of Deep-Sea Surfaces from Oblique Still Images
Estimating the area of seabed surfaces from pictures or videos is an important problem in
seafloor surveys. This task is complex to achieve with moving platforms such as submersibles,
towed or remotely operated vehicles (ROV), where the recording camera is typically
not static and provides an oblique view of the seafloor. A new method for obtaining seabed
surface area estimates is presented here, using the classical set up of two laser devices
fixed to the ROV frame projecting two parallel lines over the seabed. By combining lengths
measured directly from the image containing the laser lines, the area of seabed surfaces is
estimated, as well as the camera’s distance to the seabed, pan and tilt angles. The only
parameters required are the distance between the parallel laser lines and the camera’s horizontal
and vertical angles of view. The method was validated with a controlled in situ experiment
using a deep-sea ROV, yielding an area estimate error of 1.5%. Further applications
and generalizations of the method are discussed, with emphasis on deep-sea applications
Evaluation of the potential of aerial thermal imagery to generate 3D point clouds
This research evaluates the ability of thermal images obtained from aerial platforms to produce 3D point clouds. In this study, the thermal camera is first calibrated. Then, in order to avoid data redundancy, the key frames of the obtained thermal video are separated from other frames. Afterwards, the point clouds are generated and then the thermal ortho image is created from the key frames. The evaluation is done using visible orthophoto, ground control points and the linearity of the edges of buildings extracted from thermal images. The results of this study show that the thermal ortho image matches the visible ortho image with a good accuracy in the study area. Moreover, the standard deviation of the edges of the buildings has been calculated for a number of reconstructed buildings in thermal ortho with proper dispersion. 77% of the measurements taken from the edges of the buildings coincide with a straight line with an accuracy of better than two pixels, and about half of these values are extracted with an accuracy of better than a pixel
A semi-quantitative schlieren high-speed flow diagnostic : analysis of high-pressure-ratio, overexpanded planar flow in rocket nozzles
This work introduces a semi-quantitative schlieren (SQS) method which is used to qualitatively and quantitatively analyze complex, unsteady, compressible flows in a small, planar convergent-divergent nozzle. A basic schlieren system is used to image the evolution in time of complex supersonic flow structures, including Prandtl-Meyer expansion fans, internal shocks, near-wall oblique shocks, quasi-normal shocks, shock/boundary layer interactions, shock/shock interactions, and shock trains. The first images of shock trains in high nozzle-pressure-ratio flows are shown, and the underlying processes are described. A flow-field decomposition method is presented which allows the entire flow field to be separated into unit processes and analyzed. Various methods of analysis are presented, including a new method for the determination of node locations along a defined nozzle wall geometry using the method of characteristics. A numerical solution is developed for the analysis of a blow-down process. Computer programs which implement these solutions are presented
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