19,176 research outputs found
Bio-Inspired Stereo Vision Calibration for Dynamic Vision Sensors
Many advances have been made in the eld of computer vision. Several recent research trends
have focused on mimicking human vision by using a stereo vision system. In multi-camera systems, a
calibration process is usually implemented to improve the results accuracy. However, these systems generate
a large amount of data to be processed; therefore, a powerful computer is required and, in many cases,
this cannot be done in real time. Neuromorphic Engineering attempts to create bio-inspired systems that
mimic the information processing that takes place in the human brain. This information is encoded using
pulses (or spikes) and the generated systems are much simpler (in computational operations and resources),
which allows them to perform similar tasks with much lower power consumption, thus these processes
can be developed over specialized hardware with real-time processing. In this work, a bio-inspired stereovision
system is presented, where a calibration mechanism for this system is implemented and evaluated
using several tests. The result is a novel calibration technique for a neuromorphic stereo vision system,
implemented over specialized hardware (FPGA - Field-Programmable Gate Array), which allows obtaining
reduced latencies on hardware implementation for stand-alone systems, and working in real time.Ministerio de Economía y Competitividad TEC2016-77785-PMinisterio de Economía y Competitividad TIN2016-80644-
The Double Sphere Camera Model
Vision-based motion estimation and 3D reconstruction, which have numerous
applications (e.g., autonomous driving, navigation systems for airborne devices
and augmented reality) are receiving significant research attention. To
increase the accuracy and robustness, several researchers have recently
demonstrated the benefit of using large field-of-view cameras for such
applications. In this paper, we provide an extensive review of existing models
for large field-of-view cameras. For each model we provide projection and
unprojection functions and the subspace of points that result in valid
projection. Then, we propose the Double Sphere camera model that well fits with
large field-of-view lenses, is computationally inexpensive and has a
closed-form inverse. We evaluate the model using a calibration dataset with
several different lenses and compare the models using the metrics that are
relevant for Visual Odometry, i.e., reprojection error, as well as computation
time for projection and unprojection functions and their Jacobians. We also
provide qualitative results and discuss the performance of all models
Mirrored Light Field Video Camera Adapter
This paper proposes the design of a custom mirror-based light field camera
adapter that is cheap, simple in construction, and accessible. Mirrors of
different shape and orientation reflect the scene into an upwards-facing camera
to create an array of virtual cameras with overlapping field of view at
specified depths, and deliver video frame rate light fields. We describe the
design, construction, decoding and calibration processes of our mirror-based
light field camera adapter in preparation for an open-source release to benefit
the robotic vision community.Comment: tech report, v0.5, 15 pages, 6 figure
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers
Ultrasound (US) is the most widely used fetal imaging technique. However, US
images have limited capture range, and suffer from view dependent artefacts
such as acoustic shadows. Compounding of overlapping 3D US acquisitions into a
high-resolution volume can extend the field of view and remove image artefacts,
which is useful for retrospective analysis including population based studies.
However, such volume reconstructions require information about relative
transformations between probe positions from which the individual volumes were
acquired. In prenatal US scans, the fetus can move independently from the
mother, making external trackers such as electromagnetic or optical tracking
unable to track the motion between probe position and the moving fetus. We
provide a novel methodology for image-based tracking and volume reconstruction
by combining recent advances in deep learning and simultaneous localisation and
mapping (SLAM). Tracking semantics are established through the use of a
Residual 3D U-Net and the output is fed to the SLAM algorithm. As a proof of
concept, experiments are conducted on US volumes taken from a whole body fetal
phantom, and from the heads of real fetuses. For the fetal head segmentation,
we also introduce a novel weak annotation approach to minimise the required
manual effort for ground truth annotation. We evaluate our method
qualitatively, and quantitatively with respect to tissue discrimination
accuracy and tracking robustness.Comment: MICCAI Workshop on Perinatal, Preterm and Paediatric Image analysis
(PIPPI), 201
A practical multirobot localization system
We present a fast and precise vision-based software intended for multiple robot localization. The core component of the software is a novel and efficient algorithm for black and white pattern detection. The method is robust to variable lighting conditions, achieves sub-pixel precision and its computational complexity is independent of the processed image size. With off-the-shelf computational equipment and low-cost cameras, the core algorithm is able to process hundreds of images per second while tracking hundreds of objects with a millimeter precision. In addition, we present the method's mathematical model, which allows to estimate the expected localization precision, area of coverage, and processing speed from the camera's intrinsic parameters and hardware's processing capacity. The correctness of the presented model and performance of the algorithm in real-world conditions is verified in several experiments. Apart from the method description, we also make its source code public at \emph{http://purl.org/robotics/whycon}; so, it can be used as an enabling technology for various mobile robotic problems
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