47,834 research outputs found
Tackling 3D ToF Artifacts Through Learning and the FLAT Dataset
Scene motion, multiple reflections, and sensor noise introduce artifacts in
the depth reconstruction performed by time-of-flight cameras. We propose a
two-stage, deep-learning approach to address all of these sources of artifacts
simultaneously. We also introduce FLAT, a synthetic dataset of 2000 ToF
measurements that capture all of these nonidealities, and allows to simulate
different camera hardware. Using the Kinect 2 camera as a baseline, we show
improved reconstruction errors over state-of-the-art methods, on both simulated
and real data.Comment: ECCV 201
CED: Color Event Camera Dataset
Event cameras are novel, bio-inspired visual sensors, whose pixels output
asynchronous and independent timestamped spikes at local intensity changes,
called 'events'. Event cameras offer advantages over conventional frame-based
cameras in terms of latency, high dynamic range (HDR) and temporal resolution.
Until recently, event cameras have been limited to outputting events in the
intensity channel, however, recent advances have resulted in the development of
color event cameras, such as the Color-DAVIS346. In this work, we present and
release the first Color Event Camera Dataset (CED), containing 50 minutes of
footage with both color frames and events. CED features a wide variety of
indoor and outdoor scenes, which we hope will help drive forward event-based
vision research. We also present an extension of the event camera simulator
ESIM that enables simulation of color events. Finally, we present an evaluation
of three state-of-the-art image reconstruction methods that can be used to
convert the Color-DAVIS346 into a continuous-time, HDR, color video camera to
visualise the event stream, and for use in downstream vision applications.Comment: Conference on Computer Vision and Pattern Recognition Workshop
Micro Fourier Transform Profilometry (FTP): 3D shape measurement at 10,000 frames per second
Recent advances in imaging sensors and digital light projection technology
have facilitated a rapid progress in 3D optical sensing, enabling 3D surfaces
of complex-shaped objects to be captured with improved resolution and accuracy.
However, due to the large number of projection patterns required for phase
recovery and disambiguation, the maximum fame rates of current 3D shape
measurement techniques are still limited to the range of hundreds of frames per
second (fps). Here, we demonstrate a new 3D dynamic imaging technique, Micro
Fourier Transform Profilometry (FTP), which can capture 3D surfaces of
transient events at up to 10,000 fps based on our newly developed high-speed
fringe projection system. Compared with existing techniques, FTP has the
prominent advantage of recovering an accurate, unambiguous, and dense 3D point
cloud with only two projected patterns. Furthermore, the phase information is
encoded within a single high-frequency fringe image, thereby allowing
motion-artifact-free reconstruction of transient events with temporal
resolution of 50 microseconds. To show FTP's broad utility, we use it to
reconstruct 3D videos of 4 transient scenes: vibrating cantilevers, rotating
fan blades, bullet fired from a toy gun, and balloon's explosion triggered by a
flying dart, which were previously difficult or even unable to be captured with
conventional approaches.Comment: This manuscript was originally submitted on 30th January 1
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