The present study investigated the driving performance of older and younger drivers using a dual-task paradigm. Drivers were required to do a car-following task while detecting a signal light change in a light array above the roadway in the driving simulator under different fog conditions. Decreased accuracies and longer response times were recorded for older drivers, compared to younger drivers, especially under dense fog conditions. In addition, older drivers had decreased car following performance when simultaneously performing the light-detection task. These results suggets that under poor weather conditions (e.g. fog), with reduced visibility, older drivers may have an increased accident risk because of a decreased ability to perform multiple tasks.
Ghost free image using blur and noise estimationijcga
This paper presents an efficient image enhancement method by fusion of two different exposure images in
low-light condition. We use two degraded images with different exposures: one is a long-exposure image
that preserves the brightness but contains blur and the other is a short-exposure image that contains a lot of
noise but preserves object boundaries. The weight map used for image fusion without artifacts of blur and
noise is computed using blur and noise estimation. To get a blur map, edges in a long-exposure image are
detected at multiple scales and the amount of blur is estimated at detected edges. Also, we can get a noise
map by noise estimation using a denoised short-exposure image. Ghost effect between two successive
images is avoided according to the moving object map that is generated by a sigmoid comparison function
based on the ratio of two input images. We can get result images by fusion of two degraded images using
the weight maps. The proposed method can be extended to high dynamic range imaging without using
information of a camera response function or generating a radiance map. Experimental results with various
sets of images show the effectiveness of the proposed method in enhancing details and removing ghost
artifacts.
The Effects of Reduced Visibility from Fog on Car Following Performancejkcrash12
A study examined the effects of reduced visibility of scene information because of fog on car-following performance. Drivers were presented with a straight roadway scene in a driving simulator and were asked to maintain a predetermined driving distance in response to speed variations of a lead vehicle. Lead vehicle speed varied according to a sum of three prime sine wave frequencies. Five simulated fog density conditions and three average lead vehicle velocities were examined. Car-following performance was assessed using distance headway, variance of distance headway, root-mean-square (RMS) velocity error, control gain, phase angle, and squared coherence. Distance headway decreased only at the highest fog density condition examined. RMS velocity error increased with an increase in fog density. These results indicate that drivers had greater difficulty responding to changes in lead vehicle speed than to changes in headway. Results for squared coherence indicated that the effects of fog were greatest for the highest rate of change in lead vehicle speed (i.e., highest frequency examined). The importance of visual factors for optimal car-following performance is discussed.
Tips on Freelancing for Journalists from Elizabeth MaysElizabeth Mays
Liz Mays--writer, editor, marketer and entrepreneur--talks about freelancing to aspiring journalists--the pros, the cons and how to make it as a freelance communicator.
Opis projektu skweru sportów miejskich w Warszawie stworzonego przez wiodących warszawskich architektów młodego pokolenia przy udziale sportowców i organizatorów projektu.
Prezentacja przedstawiona Burmistrzowi Śródmieścia.
Strona projektu na facebooku:
http://www.facebook.com/group.php?gid=128656520489659&ref=ts
Ghost free image using blur and noise estimationijcga
This paper presents an efficient image enhancement method by fusion of two different exposure images in
low-light condition. We use two degraded images with different exposures: one is a long-exposure image
that preserves the brightness but contains blur and the other is a short-exposure image that contains a lot of
noise but preserves object boundaries. The weight map used for image fusion without artifacts of blur and
noise is computed using blur and noise estimation. To get a blur map, edges in a long-exposure image are
detected at multiple scales and the amount of blur is estimated at detected edges. Also, we can get a noise
map by noise estimation using a denoised short-exposure image. Ghost effect between two successive
images is avoided according to the moving object map that is generated by a sigmoid comparison function
based on the ratio of two input images. We can get result images by fusion of two degraded images using
the weight maps. The proposed method can be extended to high dynamic range imaging without using
information of a camera response function or generating a radiance map. Experimental results with various
sets of images show the effectiveness of the proposed method in enhancing details and removing ghost
artifacts.
The Effects of Reduced Visibility from Fog on Car Following Performancejkcrash12
A study examined the effects of reduced visibility of scene information because of fog on car-following performance. Drivers were presented with a straight roadway scene in a driving simulator and were asked to maintain a predetermined driving distance in response to speed variations of a lead vehicle. Lead vehicle speed varied according to a sum of three prime sine wave frequencies. Five simulated fog density conditions and three average lead vehicle velocities were examined. Car-following performance was assessed using distance headway, variance of distance headway, root-mean-square (RMS) velocity error, control gain, phase angle, and squared coherence. Distance headway decreased only at the highest fog density condition examined. RMS velocity error increased with an increase in fog density. These results indicate that drivers had greater difficulty responding to changes in lead vehicle speed than to changes in headway. Results for squared coherence indicated that the effects of fog were greatest for the highest rate of change in lead vehicle speed (i.e., highest frequency examined). The importance of visual factors for optimal car-following performance is discussed.
Tips on Freelancing for Journalists from Elizabeth MaysElizabeth Mays
Liz Mays--writer, editor, marketer and entrepreneur--talks about freelancing to aspiring journalists--the pros, the cons and how to make it as a freelance communicator.
Opis projektu skweru sportów miejskich w Warszawie stworzonego przez wiodących warszawskich architektów młodego pokolenia przy udziale sportowców i organizatorów projektu.
Prezentacja przedstawiona Burmistrzowi Śródmieścia.
Strona projektu na facebooku:
http://www.facebook.com/group.php?gid=128656520489659&ref=ts
Most face recognition algorithms are generally capable to achieve a high level of accuracy when
the image is acquired under wellcontrolled conditions. The face should be still during the acquisition
process; otherwise, the resulted image would be blur and hard for recognition. Enforcing persons to stand
still during the process is impractical; extremely likely that recognition should be performed on a blurred
image. It is important to understand the relation between the image blur and the recognition accuracy. The
ORL Database was used in the study. All images were in PGM format of 92 × 112 pixels from forty
different persons, ten images per person. Those images were randomly divided into training and testing
datasets with 50-50 ratio. Singular value decomposition was used to extract the features. The images in
the testing datasets were artificially blurred to represent a linear motion, and recognition was performed.
The blurred images were also filtered using various methods. The accuracy levels of the recognition on the
basis of the blurred faces and filtered faces were compared. The performed numerical study suggests that
at its best, the image improvement processes are capable to improve the recognition accuracy level by
less than five percent.
A cloud based approach is proposed as a solution
for preventing accidents. The system provides face detection and
eye detection from the image captured using a low cost USB
camera. Then driver’s head pose is estimated using the region of
interest computed by Viola-Jones algorithm. The system also
contains a heart rate sensor for detecting the biological problems
of the driver and an alcohol sensor to detect whether the driver
has consumed alcohol or not. This combined system is used to
prevent drink and drive accident, accident due to inattention of
driver and accident due to driver’s biomedical problems.
Driving without license is the major cause for the road accident and the equivalent monetary losses. This paper is based on virtual reality based driving system which would enhance road safety and vehicle security. This paper helps to limit the vehicle operation on the basics of two parameters-Learn the driving by our own, category (car or bike) of the vehicle for which the driving license is issued. The hardware and software system required to improve our safety and security is developed. This driving system is apt for getting the license without bribe by gathering eye-gaze, Electroencephalography and peripheral physiological data.
Palinko Estimating Cognitive Load Using Remote Eye Tracking In A Driving Simu...Kalle
We report on the results of a study in which pairs of subjects were involved in spoken dialogues and one of the subjects also operated a simulated vehicle. We estimated the driver’s cognitive load based on pupil size measurements from a remote eye tracker. We compared the cognitive load estimates based on the physiological pupillometric data and driving performance data. The physiological and performance measures show high correspondence suggesting that remote eye tracking might provide reliable driver cognitive load estimation, especially in simulators. We also introduced a new pupillometric cognitive load measure that shows promise in tracking cognitive load changes on time scales of several seconds.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
SINGLE IMAGE SUPER RESOLUTION: A COMPARATIVE STUDYcsandit
The majority of applications requiring high resolution images to derive and analyze data
accurately and easily. Image super resolution is playing an effective role in those applications.
Image super resolution is the process of producing high resolution image from low resolution
image. In this paper, we study various image super resolution techniques with respect to the
quality of results and processing time. This comparative study introduces a comparison between
four algorithms of single image super-resolution. For fair comparison, the compared algorithms
are tested on the same dataset and same platform to show the major advantages of one over the
others.
Presentation by Sanna Pampel, Research Student at the Institute for Transport Studies (ITS), delivered as part of the Institute's seminar series.
www.its.leeds.ac.uk/people/s.pampel
www.its.leeds.ac.uk/about/events/seminar-series/
Enhanced Face Detection Based on Haar-Like and MB-LBP FeaturesDr. Amarjeet Singh
The effective real-time face detection framework
proposed by Viola and Jones gained much popularity due its
computational efficiency and its simplicity. A notable
variant replaces the original Haar-like features with MBLBP (Multi-Block Local Binary Pattern) which are defined
by the local binary pattern operator, both detector types are
integrated into the OpenCV library. However, each
descriptor and its evaluation method has its own set of
strengths and setbacks. In this paper, an enhanced two-layer
face detector composed of both Haar-like and MB-LBP
features is presented. Haar-like features are employed as a
coarse filter but with a new evaluation involving dual
threshold. The already established MB-LBPs are arranged
as the fine filter of the detector. The Gentle AdaBoost
learning algorithm is deployed for the training of the
proposed detector to reach the classification and
performance potential. Experiments show that in the early
stages of classification, Haar features with dual threshold
are more discriminative than MB-LBP and original Haarlike features with respect to number of features required
and computation. Benchmarking the proposed detector
demonstrate overall 12% higher detection rate at 17% false
alarm over using MB-LBP features singly while performing
with ×3 speedup.
Development of Nighttime Visibility Assessment System for road using a Low Li...inventionjournals
Although the numbers of traffic accidents and fatalities in Korea have been decreased constantly, traffic accidents during night time have not been decreased. Thus, it is necessary to conduct comprehensive studies that can investigate, analyze, and assess the visibility environment of drivers in order to ensure safety in roads during nighttime. The purpose of this study is to develop the technology of acquiring and analyzing the nighttime driving environment in roads from driver's viewpoints. For this purpose, this study suggests a nighttime visibility assessment system that can quantify suitability. To do this, this study defined driver's visibility and selected effectiveness scale thereby developing an assessment model that reflected driver's level of recognition. The suggested system is developed consisting of two parts: the investigation device using a low light cameraequipped with investigation program and the web-based assessment program utilizing the document database. In the future, verification on the system will be conducted under various drivers’ visual environments and pilot field application will be planned to improve accuracy of assessment on nighttime road visibility based on the system.
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Most face recognition algorithms are generally capable to achieve a high level of accuracy when
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process; otherwise, the resulted image would be blur and hard for recognition. Enforcing persons to stand
still during the process is impractical; extremely likely that recognition should be performed on a blurred
image. It is important to understand the relation between the image blur and the recognition accuracy. The
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contains a heart rate sensor for detecting the biological problems
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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accurately and easily. Image super resolution is playing an effective role in those applications.
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image. In this paper, we study various image super resolution techniques with respect to the
quality of results and processing time. This comparative study introduces a comparison between
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www.its.leeds.ac.uk/people/s.pampel
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proposed by Viola and Jones gained much popularity due its
computational efficiency and its simplicity. A notable
variant replaces the original Haar-like features with MBLBP (Multi-Block Local Binary Pattern) which are defined
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integrated into the OpenCV library. However, each
descriptor and its evaluation method has its own set of
strengths and setbacks. In this paper, an enhanced two-layer
face detector composed of both Haar-like and MB-LBP
features is presented. Haar-like features are employed as a
coarse filter but with a new evaluation involving dual
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learning algorithm is deployed for the training of the
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performance potential. Experiments show that in the early
stages of classification, Haar features with dual threshold
are more discriminative than MB-LBP and original Haarlike features with respect to number of features required
and computation. Benchmarking the proposed detector
demonstrate overall 12% higher detection rate at 17% false
alarm over using MB-LBP features singly while performing
with ×3 speedup.
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Age-related Driving Performance: Effect of fog under dual-task conditions
1. PROCEEDINGS of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
AGE-RELATED DRIVING PERFORMANCE:
EFFECT OF FOG UNDER DUAL-TASK CONDITIONS
Rui Ni, Julie Kang, and George J. Andersen
Department of Psychology
University of California Riverside
Riverside, California, USA
E-mail: ruini@ucr.edu
Summary: The present study investigated the driving performance of older and
younger drivers using a dual-task paradigm. Drivers were requred to do a
car-following task while detecting a signal light change in a light array above the
roadway in the driving simulator under different fog conditions. Decreased
accuracies and longer response times were recorded for older drivers, compared to
younger drivers, expecially under dense fog conditions. In addition, older drivers had
decreased car following performance when simultaneously performing the
light-detection task. These results suggets that under poor weather conditions (e.g.
fog), with reduced visibility, older drivers may have an increased accident risk
because of a decreased ability to perform multiple tasks.
INTRODUCTION
Previous research has documented age-related decrements in visual performance. These studies
have included driving-related tasks such as steering control and collision detection (Andersen &
Sauer, 2004; Ni, Andersen, and Rizzo, 2005; Andersen & Enriquez, 2006). Other studies have
shown performance decrements when performing multiple tasks (Kramer & Larish, 1996). The
objectives of the present study were twofold. First, to examine the age-related effects of
performing multiple driving tasks, and second, to determine whether simulated inclement weather
(i.e., fog) will differentially affect the performance of older drivers because of reduced contrast of
the driving scene.
Driving simulation displays depicted a roadway scene of city blocks with traffic in two adjacent
lanes and a vehicle located directly in front of the driver’s vehicle. Drivers were asked to perform a
car-following task and to detect a light change in an array of lights located above the roadway. For
the car-following task drivers were shown an initial period of constant speed and fixed distance
behind the lead vehicle. After the initial period, the lead vehicle speed changed according to a sum
of 3 sine wave functions, and drivers were asked to maintain the initial driving distance. When the
driver’s vehicle arrived at a pre-specified distance from the light array, one of the lights changed
and drivers were asked to indicate whether the light change occurred on the left or right side of the
array. To measure the effect of foggy weather, we systematically varied the fog condition from
clear (i.e., no fog) to dense fog (shown in Figure 1).
365
2. PROCEEDINGS of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
Experiment
Drivers. Eight older drivers (mean age =75) and
8 younger drivers (mean age=23) paticipated in a
dual-task performance study using a driving
simulator. All drivers had a minimum of 2 years
of driving experience, had normal or corrected to
normal vision, and were naïve to the purpose of
the experiment.
Apparatus. The displays were presented on a
Dell PC computer system. The display has a
a
visual angle of 47 deg by 26 deg, with the refresh
rate at 60 Hz and the resolution at 1024 by 768.
A Logitech Wingman FomulaGP control system,
including acceleration and brake pedals, was
used for closed-loop control of the simulator.
Drivers viewed the displays binocularly at a
distance of approximately 60 cm from the
screen.
Stimuli. The driving simulation depicted a
roadway scene of city blocks with traffic in two
adjacent lanes and a vehicle located directly in
front of the driver’s vehicle. An array of signal b
lights either in red or green was located above
the roadway. The array consisted of 21 lights
with 10 lights on the right, 10 on the left and one
aligned with the center of the driver’s position.
The light change occurred at either the 3rd, 6th,
or 9th light location from the center light (0
position) and occurred on either the right or left
side.
c
Figure 1. Three fog conditions in the
experiment. a, no fog; b, medium fog; and
c, dense fog.
366
3. PROCEEDINGS of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
Design. The independent variables were fog density (no fog, medium fog, and dense fog), the
horizontal position of the light when a change occurred (3rd, 6th or 9th position), and the location
of the light change (left or right). These variables were run as within-subjects variables. Age group
(younger vs. older) was run as a between-subjects variable. The dependent variables were
accuracy and response time (for the light-change detection task), and speed difference between the
driver’s vehicle and the lead vehicle (for the car-following task).
Procedure. Two tasks were examined: car following and detecting a light change. For the
car-following task, drivers were required to keep a constant distance behind the lead vehicle,
which varied its speed after an initial period of travelling. For the light-detection task, drivers were
asked to respond to a light change in an array of lights located above the roadway. Drivers
performed both single and dual-task conditions. No fog was simulated in the single-task baseline
conditions and the light-change task involved a change at the 3rd position. In the other sessions, 3
fog conditions were employed: no fog, medium fog, and dense fog.
Results of light detection t ask in Dual-t ask condition
1 .2
1 .1
Ratio of accuracy to baseline measurement
1 .0
Younger Drivers
0 .9 Older Drivers
0 .8
0 .7
0 .6
0 .5
Fog: No Medium Dense Fog: No Mediu m Dense Fog: No Medium Dense
position: 3 Position: 6 Position 9
Figure 2. The performance on light-detection task in dual-task condition for two
age groups. The dependent variable is the ratio of judgment accuracy in
dual-task condition to that in baseline condition.
367
4. PROCEEDINGS of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
RESULTS
For the light-detection task a 2 (task condition, i.e., single, and dual-task) by 3 (fog condition) by 3
(light change position) analysis of variance (ANOVA) was used to analyze mean accuracy and
response time for each driver in the two age groups. With regard to accuracy (shown in Figure 2),
the main effect of task condition (single vs. dual) was significant (F (1, 14) =15.661, p<0.01).
Significant differences were also found between younger and older drivers (F (1, 14) =9.4023,
p<0.01). The results showed that accuracy was greater in the single-task than in dual-task
condition and was greater for younger drivers as compared to older drivers. Significant
interactions were also found between task condition and age group (F(1, 14)=6.2360, p<0.05),
between task condition and light-change position (F(2, 28)=4.9903, p<0.05), between task
condition, fog density and light-change position (F(4, 56)=2.8796, p<0.05), and between task
condition, fog density, light-change position, and age group (F(4, 56)=2.6343, p<0.05). These
results indicate that older drivers, compared to younger drivers, were less accurate at detecting a
light change under dense fog conditions when performing two tasks simultaneously.
2 .1
Young Drivers
2 .0
Old Drivers
Ratio of response time to basline measurment
1 .9
1 .8
1 .7
1 .6
1 .5
1 .4
1 .3
1 .2
Position 6 Position 6 Position 6
3 9 3 9 3 9
No Fog Medium Fog Dense Fog
Figure 3. Performance for the light-detection task for younger and older
drivers. The dependent variable is the ratio of dual task response time/baseline
single task response time.
368
5. PROCEEDINGS of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
With regard to response time (see Figure 3), a significant effect was found for task condition (F(1,
14)=7.4555, p<0.05), fog density (F(2, 28)=16.678, p<0.01), and light-change position ( F(2,
28)=19.281, p<0.01). In addition, significant interactions were found between fog density,
light-change position, and age group (F(4, 56)=3.6258, p<0.05), and between task condition, fog
density, light-change position, and age group (F(4, 56)=3.0167, p<0.05). These results indicate
that older drivers had longer response times to detect a light change under simulated foggy weather,
especially when the position of light change was more peripheral.
An ANOVA of car-following performance was performed based on the speed difference between
the driver’s and lead vehicle (see Figure 4). The main effect of task condition (F(1, 14)=73.903,
p<0.01) was significant, as well as the main effect of fog density (F(2, 28)=4.1746, p< 0.05). A
significant interaction was found between task condition and fog density (F(2, 28)=4.5020,
p<0.05). Although no significant effect of age was found, we found that older drivers had greater
error in following the lead vehicle in the dual-task condition (F(1, 14)=7.2812, p<0.05).
1.8
Young Drivers
Older Drivers
1.6
Ratio of RMS to the baseline measurement
1.4
1.2
1.0
0.8
0.6
0.4
Fog: No Medium Dense Fog: No Medium Dense
Single-task condition Dual-task condition
Figure 4. Car-following performance for younger and older drivers. The
dependent variable is the ratio of RMS dual-task RMS error/baseline single
task RMS error.
369
6. PROCEEDINGS of the Fourth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design
DISCUSSION
These results indicate less accuracy and longer response times to detect a light change for older
drivers, as compared to younger drivers, especially when visibility is reduced. When attending to a
secondary task (i.e,. light-change detection) older drivers, as compared to younger drivers, had
greater error in car-following performance. These results suggest that under poor weather
conditions with reduced visibility, older drivers may have an increased risk of accidents because of
a decreased ability to perform multiple tasks.
ACKNOWLEDGMENTS
This research was supported by NIA grant NIH AG13419-06 and contract 65A0162 from the
California Department of Transportation.
REFERENCES
Andersen, G.J., Sauer, C.W. (2004). Optical information for collision detection during deceleration.
In Advances in psychology, Vol 135: Time-to-contact. Amsterdam, Netherlands: Elsevier
Science Publishers B.V.
Andersen, G.J, Enriquez, A. (2006). Aging and the Detection of Observer and Moving Object
Collisions. Psychology and aging, 21(1), 74-85.
Kramer, A.F., & Larish, J. (1996). Aging and dual-task performance. In W. Rogers, A.D. Fisk, & N.
Walker (Eds.), Aging and skilled performance. Hillsdale, NJ: Erlbaum, 83-112.
Ni, R., Andersen, G.J., and Rizzo, M. (2005). Age related decrements in steering control: The
effects of landmark and optical flow information. Proceedings of the Third International
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