19,065 research outputs found
Temporal shape super-resolution by intra-frame motion encoding using high-fps structured light
One of the solutions of depth imaging of moving scene is to project a static
pattern on the object and use just a single image for reconstruction. However,
if the motion of the object is too fast with respect to the exposure time of
the image sensor, patterns on the captured image are blurred and reconstruction
fails. In this paper, we impose multiple projection patterns into each single
captured image to realize temporal super resolution of the depth image
sequences. With our method, multiple patterns are projected onto the object
with higher fps than possible with a camera. In this case, the observed pattern
varies depending on the depth and motion of the object, so we can extract
temporal information of the scene from each single image. The decoding process
is realized using a learning-based approach where no geometric calibration is
needed. Experiments confirm the effectiveness of our method where sequential
shapes are reconstructed from a single image. Both quantitative evaluations and
comparisons with recent techniques were also conducted.Comment: 9 pages, Published at the International Conference on Computer Vision
(ICCV 2017
A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry
The demand for autonomous vehicles is increasing gradually owing to their
enormous potential benefits. However, several challenges, such as vehicle
localization, are involved in the development of autonomous vehicles. A simple
and secure algorithm for vehicle positioning is proposed herein without
massively modifying the existing transportation infrastructure. For vehicle
localization, vehicles on the road are classified into two categories: host
vehicles (HVs) are the ones used to estimate other vehicles' positions and
forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV
transmits modulated data from the tail (or back) light, and the camera of the
HV receives that signal using optical camera communication (OCC). In addition,
the streetlight (SL) data are considered to ensure the position accuracy of the
HV. Determining the HV position minimizes the relative position variation
between the HV and FV. Using photogrammetry, the distance between FV or SL and
the camera of the HV is calculated by measuring the occupied image area on the
image sensor. Comparing the change in distance between HV and SLs with the
change in distance between HV and FV, the positions of FVs are determined. The
performance of the proposed technique is analyzed, and the results indicate a
significant improvement in performance. The experimental distance measurement
validated the feasibility of the proposed scheme
Optimal Radiometric Calibration for Camera-Display Communication
We present a novel method for communicating between a camera and display by
embedding and recovering hidden and dynamic information within a displayed
image. A handheld camera pointed at the display can receive not only the
display image, but also the underlying message. These active scenes are
fundamentally different from traditional passive scenes like QR codes because
image formation is based on display emittance, not surface reflectance.
Detecting and decoding the message requires careful photometric modeling for
computational message recovery. Unlike standard watermarking and steganography
methods that lie outside the domain of computer vision, our message recovery
algorithm uses illumination to optically communicate hidden messages in real
world scenes. The key innovation of our approach is an algorithm that performs
simultaneous radiometric calibration and message recovery in one convex
optimization problem. By modeling the photometry of the system using a
camera-display transfer function (CDTF), we derive a physics-based kernel
function for support vector machine classification. We demonstrate that our
method of optimal online radiometric calibration (OORC) leads to an efficient
and robust algorithm for computational messaging between nine commercial
cameras and displays.Comment: 10 pages, Submitted to CVPR 201
An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System
Optical camera communication (OCC) exhibits considerable importance nowadays
in various indoor camera based services such as smart home and robot-based
automation. An android smart phone camera that is mounted on a mobile robot
(MR) offers a uniform communication distance when the camera remains at the
same level that can reduce the communication error rate. Indoor mobile robot
navigation (MRN) is considered to be a promising OCC application in which the
white light emitting diodes (LEDs) and an MR camera are used as transmitters
and receiver respectively. Positioning is a key issue in MRN systems in terms
of accuracy, data rate, and distance. We propose an indoor navigation and
positioning combined algorithm and further evaluate its performance. An android
application is developed to support data acquisition from multiple simultaneous
transmitter links. Experimentally, we received data from four links which are
required to ensure a higher positioning accuracy
Estimating Carotid Pulse and Breathing Rate from Near-infrared Video of the Neck
Objective: Non-contact physiological measurement is a growing research area
that allows capturing vital signs such as heart rate (HR) and breathing rate
(BR) comfortably and unobtrusively with remote devices. However, most of the
approaches work only in bright environments in which subtle
photoplethysmographic and ballistocardiographic signals can be easily analyzed
and/or require expensive and custom hardware to perform the measurements.
Approach: This work introduces a low-cost method to measure subtle motions
associated with the carotid pulse and breathing movement from the neck using
near-infrared (NIR) video imaging. A skin reflection model of the neck was
established to provide a theoretical foundation for the method. In particular,
the method relies on template matching for neck detection, Principal Component
Analysis for feature extraction, and Hidden Markov Models for data smoothing.
Main Results: We compared the estimated HR and BR measures with ones provided
by an FDA-cleared device in a 12-participant laboratory study: the estimates
achieved a mean absolute error of 0.36 beats per minute and 0.24 breaths per
minute under both bright and dark lighting.
Significance: This work advances the possibilities of non-contact
physiological measurement in real-life conditions in which environmental
illumination is limited and in which the face of the person is not readily
available or needs to be protected. Due to the increasing availability of NIR
imaging devices, the described methods are readily scalable.Comment: 21 pages, 15 figure
Image enhancement from a stabilised video sequence
The aim of video stabilisation is to create a new video sequence where the motions (i.e. rotations, translations) and scale differences between frames (or parts of a frame) have effectively been removed. These stabilisation effects can be obtained via digital video processing techniques which use the information extracted from the video sequence itself, with no need for additional hardware or knowledge about camera physical motion.
A video sequence usually contains a large overlap between successive frames, and regions of the same scene are sampled at different positions. In this paper, this multiple sampling is combined to achieve images with a higher spatial resolution. Higher resolution imagery play an important role in assisting in the identification of people, vehicles, structures or objects of interest captured by surveillance cameras or by video cameras used in face recognition, traffic monitoring, traffic law reinforcement, driver assistance and automatic vehicle guidance systems
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