5,885 research outputs found
A Reproducible Study on Remote Heart Rate Measurement
This paper studies the problem of reproducible research in remote
photoplethysmography (rPPG). Most of the work published in this domain is
assessed on privately-owned databases, making it difficult to evaluate proposed
algorithms in a standard and principled manner. As a consequence, we present a
new, publicly available database containing a relatively large number of
subjects recorded under two different lighting conditions. Also, three
state-of-the-art rPPG algorithms from the literature were selected, implemented
and released as open source free software. After a thorough, unbiased
experimental evaluation in various settings, it is shown that none of the
selected algorithms is precise enough to be used in a real-world scenario
Reviewing and extending the five-user assumption: A grounded procedure for interaction evaluation
" © ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Computer-Human Interaction (TOCHI), {VOL 20, ISS 5, (November 2013)} http://doi.acm.org/10.1145/2506210 "The debate concerning how many participants represents a sufficient number for interaction testing is
well-established and long-running, with prominent contributions arguing that five users provide a good
benchmark when seeking to discover interaction problems. We argue that adoption of five users in this
context is often done with little understanding of the basis for, or implications of, the decision. We present
an analysis of relevant research to clarify the meaning of the five-user assumption and to examine the
way in which the original research that suggested it has been applied. This includes its blind adoption and
application in some studies, and complaints about its inadequacies in others. We argue that the five-user
assumption is often misunderstood, not only in the field of Human-Computer Interaction, but also in fields
such as medical device design, or in business and information applications. The analysis that we present
allows us to define a systematic approach for monitoring the sample discovery likelihood, in formative and
summative evaluations, and for gathering information in order to make critical decisions during the
interaction testing, while respecting the aim of the evaluation and allotted budget. This approach â which
we call the âGrounded Procedureâ â is introduced and its value argued.The MATCH programme (EPSRC Grants: EP/F063822/1 EP/G012393/1
A Comparative Evaluation of Heart Rate Estimation Methods using Face Videos
This paper presents a comparative evaluation of methods for remote heart rate
estimation using face videos, i.e., given a video sequence of the face as
input, methods to process it to obtain a robust estimation of the subjects
heart rate at each moment. Four alternatives from the literature are tested,
three based in hand crafted approaches and one based on deep learning. The
methods are compared using RGB videos from the COHFACE database. Experiments
show that the learning-based method achieves much better accuracy than the hand
crafted ones. The low error rate achieved by the learning based model makes
possible its application in real scenarios, e.g. in medical or sports
environments.Comment: Accepted in "IEEE International Workshop on Medical Computing
(MediComp) 2020
SLM-based Digital Adaptive Coronagraphy: Current Status and Capabilities
Active coronagraphy is deemed to play a key role for the next generation of
high-contrast instruments, notably in order to deal with large segmented
mirrors that might exhibit time-dependent pupil merit function, caused by
missing or defective segments. To this purpose, we recently introduced a new
technological framework called digital adaptive coronagraphy (DAC), making use
of liquid-crystal spatial light modulators (SLMs) display panels operating as
active focal-plane phase mask coronagraphs. Here, we first review the latest
contrast performance, measured in laboratory conditions with monochromatic
visible light, and describe a few potential pathways to improve SLM
coronagraphic nulling in the future. We then unveil a few unique capabilities
of SLM-based DAC that were recently, or are currently in the process of being,
demonstrated in our laboratory, including NCPA wavefront sensing,
aperture-matched adaptive phase masks, coronagraphic nulling of multiple star
systems, and coherent differential imaging (CDI).Comment: 14 pages, 9 figures, to appear in Proceedings of the SPIE, paper
10706-9
Inverse problem of photoelastic fringe mapping using neural networks
This paper presents an enhanced technique for inverse analysis of photoelastic fringes using neural networks to determine the applied load. The technique may be useful in whole-field analysis of photoelastic images obtained due to external loading, which may find application in a variety of specialized areas including robotics and biomedical engineering. The presented technique is easy to implement, does not require much computation and can cope well within slight experimental variations. The technique requires image acquisition, filtering and data extraction, which is then fed to the neural network to provide load as output. This technique can be efficiently implemented for determining the applied load in applications where repeated loading is one of the main considerations. The results presented in this paper demonstrate the novelty of this technique to solve the inverse problem from direct image data. It has been shown that the presented technique offers better result for the inverse photoelastic problems than previously published works
Towards Robust Curve Text Detection with Conditional Spatial Expansion
It is challenging to detect curve texts due to their irregular shapes and
varying sizes. In this paper, we first investigate the deficiency of the
existing curve detection methods and then propose a novel Conditional Spatial
Expansion (CSE) mechanism to improve the performance of curve text detection.
Instead of regarding the curve text detection as a polygon regression or a
segmentation problem, we treat it as a region expansion process. Our CSE starts
with a seed arbitrarily initialized within a text region and progressively
merges neighborhood regions based on the extracted local features by a CNN and
contextual information of merged regions. The CSE is highly parameterized and
can be seamlessly integrated into existing object detection frameworks.
Enhanced by the data-dependent CSE mechanism, our curve text detection system
provides robust instance-level text region extraction with minimal
post-processing. The analysis experiment shows that our CSE can handle texts
with various shapes, sizes, and orientations, and can effectively suppress the
false-positives coming from text-like textures or unexpected texts included in
the same RoI. Compared with the existing curve text detection algorithms, our
method is more robust and enjoys a simpler processing flow. It also creates a
new state-of-art performance on curve text benchmarks with F-score of up to
78.4.Comment: This paper has been accepted by IEEE International Conference on
Computer Vision and Pattern Recognition (CVPR 2019
Understanding user experience of mobile video: Framework, measurement, and optimization
Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the userâs interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining usersâ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account userâs needs and desires when using the service, emphasizing the userâs overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study
- âŠ