Received: 22 August 2022
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Revised: 17 December 2022
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Accepted: 23 December 2022
DOI: 10.1111/1556-4029.15191
TECHNICAL NOTE
Digital & Multimedia Sciences
Determination of vehicle speed from recorded video using the
open-­source software Kinovea
Saverio Paolino | Francesco Zampa MSc
Reparto Carabinieri Investigazioni
Scientifiche (R.I.S.), Parma, Italy
Correspondence
Francesco Zampa, MSc, Reparto
Carabinieri Investigazioni Scientifiche,
Strada delle Fonderie 2, Parma 43125,
Italy.
Email: zampa.francesco@gmail.com
Abstract
Video devices of different kind often record traffic accidents, including vehicle-­
pedestrian collisions and hit-­and-­run accidents. In these cases, the vehicle speed is
valuable information because it can assist the investigators in an accident reconstruction. This paper examines the use of Kinovea, an open-­source video annotation tool
designed for sport analysis, to estimate vehicle speed in forensic videos. Kinovea does
not require a complex methodology, and it can be used to make the calculation easily.
A series of vehicle driving experiments using an appropriately calibrated speed radar
system (so called Scout Speed) were carried out, and measurements were compared
with the estimated speed. In controlled conditions, the comparison of Scout reference
speed and calculated average vehicle speed by means of Kinovea found an average
difference of 0.43 km/h, with a margin of error of ±0.64 km/h. In addition, further
preliminary tests were carried out to check the reliability of the measurements under
lower resolution conditions. Also, in these cases the calculations were in line with the
ground truth. Therefore, in the tested conditions, Kinovea demonstrated to be an
easy and reliable tool available for forensic video examiners. Further tests need to be
conducted in order to address the applicability of the measurement technique with
true CCTV/surveillance video recordings.
KEYWORDS
accident reconstruction, forensic photogrammetry, forensic video analysis, Kinovea, speed
calculation
Highlights
• Video devices of different kind often record the passage of vehicles involved in traffic
accidents.
• The measurement of the speed of a vehicle from a video provides a valuable information in an
accident reconstruction.
• Kinovea, a video annotation tool, can be used to estimate a vehicle speed in forensic videos
captured by stationary cameras.
• When the necessary requirements are satisfied, Kinovea demonstrated to be an easy and
reliable tool.
J Forensic Sci. 2023;68:667–675.
wileyonlinelibrary.com/journal/jfo
© 2022 American Academy of Forensic Sciences.
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667
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1
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PAOLINO and ZAMPA
I NTRO D U C TI O N
under controlled conditions, further preliminary tests were carried
out to check the reliability of the measurements under lower reso-
Video devices of different kind often record traffic accidents, includ-
lution conditions.
ing vehicle–­pedestrian collisions and hit-­and-­run accidents. In these
cases, the vehicle speed is a valuable information because it can assist the investigators in an accident reconstruction, especially when
there is insufficient evidence at the scene (e.g., skid marks) [1, 2].
An early work was reported by Compton et al. [3] that calcu-
2
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M ATE R I A L S A N D M E TH O DS
2.1 | Driving test and setup of cameras
lated the vehicle speed by a simple distance–­time calculation. The
location of the vehicle was, however, made either through obser-
The driving test was performed on a freeway closed to traffic for
vation by independent assessors or through comparison with some
the duration of the experiment. A sufficiently long and straight
reference points. Different methods have been proposed over the
stretch of the road was chosen. As shown in Figure 1, a rectangle
years to obtain the vehicle speed from a stationary camera [4–­6].
of (4 m × 7 m) was marked on the road using four white cardboards
Independently of the specific method, photogrammetry [7] is gener-
sheets (A4 format) secured by bi-­adhesive tape.
ally used to estimate the distance while the knowledge of the timing
Three stationary cameras (JVC GS-­TD1BE, CANON XF405, and
of the recording systems is used to get the time difference. Based
JVC GY-­HM750E) were installed on tripods, one perpendicular to
on this, the average speed of the vehicle between two frames can
the straight road and the others with (opposite) angle views of about
be calculated.
30° with respect to the road. (Figure 2).
Kinovea is a video annotation tool designed for sport analysis [8].
It features utilities to capture, slow down, compare, annotate, and
Multiple angle views were used in order to verify a possible influence on the measurements.
measure motion in videos. Kinovea is completely free and open
The frame rate of the obtained videos was 29.97 frames per sec-
source. The video player is based on the FFmpeg libraries and thus
ond (fps) for the JVC GS-­TD1BE camera and 25 fps for the other two.
can decode video encoded to a supported format specification. It
The evaluation of frame rate in recorded videos was performed ex-
should be noted that FFmpeg may not properly decode proprietary
ploiting the Amped FIVE [9] file info-­frame analysis tool. The ffprobe
video file formats often found in CCTV video files. The user inter-
reports generated by the Amped FIVE tool are shown in Table A1 in
face is also available in 26 languages.
Appendix 1 for each camera. In addition, a cell phone stopwatch dis-
This article proposes the use of Kinovea to estimate a vehicle
playing hours, minutes, second, and fractions was used as external
speed in forensic videos captured by stationary cameras. Kinovea
timing source through recording a test video for each camera. These
does not require a complex methodology and it can be used to make
analyses allowed to verify that the frame rate of each camera was
the calculation easily. Vehicle driving experiments were carried out
constant all over the recorded videos [10]. It is important to perform
using an appropriately calibrated speed radar system (Scout Speed)
this analysis before using Kinovea. Indeed, being that the software
and comparing its measurements with the estimated speed in order
uses the FFmpeg libraries, it will default to a constant frame rate
to assess the usefulness of Kinovea in real traffic accident cases. The
when it cannot decode wrapper timing information.
first objective of these tests was to verify if the calculations made by
All the cameras had a full-­HD resolution of 1920 × 1080 pixels
means of Kinovea were reliable. Therefore, the selection of the cam-
and were setup to deliver video in an interlaced manner. It is import-
eras was done to limit the source of uncertainty often given by the
ant to note that Kinovea can only be applied to videos captured by
technical features of the CCTVs. Once demonstrated the accuracy
stationary cameras, being pan-­tilt cameras excluded.
F I G U R E 1 Four points constituting
the vertices of the rectangle marked on
the road. [Colour figure can be viewed at
wileyonlinelibrary.com]
15564029, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/1556-4029.15191 by Universidad Nacional Autonoma De Mexico, Wiley Online Library on [15/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
668
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2.2 | Speed measurement by means of Kinovea
Amped FIVE software (ver. 25.587) was used prior to examination in
Kinovea to correct for lens distortion by means of the “Fisheye correction” tool. Then, Kinovea (ver 0.9.5) was used for speed measurements. The frames immediately before the reference rectangle on the
street were taken. For each speed and camera, a variable number of
frames were considered, resulting in an average value of the speed.
The followed procedure was used to estimate speed.
a. By means of the perspective grid function of Kinovea a rectanF I G U R E 2 Position of the cameras with respect of the section
of the road where the tests were carried out. [Colour figure can be
viewed at wileyonlinelibrary.com]
gle is drawn (Figure 4A) considering the reference points on the
street that were noted on purpose. In casework, it is important
to have these reference points available considering specific elements on the video.
b. By means of the calibrate function (Figure 4B) it is possible to
insert the actual measurements of the sides of the rectangle.
c. The first useful frame is considered, that is the one in which there
are no obstacles that limit the vision, and the vehicle is less than
five meters away from the reference points traced on the road. To
measure vehicle position in the video, the contact point of the tire
of the car wheel with the road surface was set as the tracking point.
It is important that this point stands on the same plane of the rectangle used for the calibration. Clicking on this point with the right
mouse button, the function Track path can be activated and a double rectangle with a central cross will appear on the image which
will be the precise point of our pointing with the mouse. (Figure 5)
d. From the configuration menu, measurement—­speed has to be selected. (Figure 6)
The two rectangles in Figure 6 are used by Kinovea to run the
tracking described in the next point (e).
e. The car can be then tracked by scrolling the video one frame at a
time. The software will try to automatically identify the tracking
point frame by frame; in case of mistake, it will be possible to position it correctly by clicking on it with the left button (Figure 7).
It is intended that any obstacle (e.g., a light pole) between the
camera and the vehicle negatively affects the automatic tracking.
F I G U R E 3 Scout speed installed in the test vehicle. [Colour
figure can be viewed at wileyonlinelibrary.com]
In order to identify video frames to be utilized in the calculations,
a visual macroblock analysis was performed using the Amped FIVE
verification-­macroblock analysis tool [11]. This allowed to select only
The Scout Speed (Figure 3) was installed in the test vehicle. This
system was used to obtain the effective speed of the vehicle with
frames that consisted of newly encoded information in order to accurately place the reference point considered on the car wheel.
an error of ±2 km/h (data extracted from the calibration certificate
during the validity period).
f. To end the editing, the last frame of interest will be selected
The test driver on board was instructed to drive the vehicle at
activating the End path edition function with a right click of the
constant speed along the measurement area. In order to achieve it, a
mouse on the cross. The average speed of the vehicle will now be
suitable run-­up was taken, and the cruise control was exploited. Five
superimposed in the image, frame by frame. (Figure 8)
increasing speeds were considered (30, 50, 70, 90, and 110 km/h),
and two set of data were registered for each one. This means that
the car drove by twice at each speed and each pass was used.
Measurements can be exported for further processing in external applications as csv format file using the kinematics dialog.
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PAOLINO and ZAMPA
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PAOLINO and ZAMPA
F I G U R E 4 Kinovea—­(A) on the left: Perspective grid function. The violet grid is the rectangle used to calibrate the image. (B) on the right:
Calibrate function. [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 5 Kinovea—­Track path
function. [Colour figure can be viewed at
wileyonlinelibrary.com]
2.3 | Preliminary tests under lower
resolution conditions
Then, Kinovea was used for speed measurements as explained in
the previous section, skipping the visual macroblock analysis. Only
one camera and only one pass at each speed were analyzed.
Once verified the accuracy under controlled conditions, further pre-
Variable frame rates were not considered for these tests. When
liminary tests were carried out to check the reliability of the meas-
dealing with a video with variable frame rates, it was observed that
urements under lower resolution conditions.
Kinovea automatically considered the average frame rate. Therefore,
Two scenarios were set up, namely LowerRes #1 and LowerRes #2:
the speed calculation could be consequently affected. This constitutes a limitation to be considered in the use of Kinovea that de-
• LowerRes #1—­the original CANON XF405 videos were down-
serves further tests.
scaled to a 768 × 432 pixels resolution and compressed using the
file format H.264.
• LowerRes #2—­the original CANON XF405 videos were down-
2.4 | Uncertainty measurements
scaled to a 768 × 432 pixels resolution and compressed using the
file format H.264. In addition, the frame rate was converted to 10
Kinovea does not include the calculation of uncertainty measurements.
fps.
An estimation has been done taking into account the factors discussed
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670
671
F I G U R E 6 Kinovea—­Configuration
menu. [Colour figure can be viewed at
wileyonlinelibrary.com]
F I G U R E 7 Kinovea—­The tracking
(yellow line) of the reference point located
on the vehicle. [Colour figure can be
viewed at wileyonlinelibrary.com]
in [12]. The physical dimension of a pixel found the same distance from
accurately define the specific reference point, a margin of error was
the camera as the vehicle was calculated. In order to accomplish this,
deemed for each condition. As for the elapsed time, a ± 1 fps was used.
a roadway lane stripe was measured on scene, and the same stripe
The values estimated for the 25 fps cameras have been extended to
was measured in Amped FIVE. Then, considering examiner's ability to
the 29.97 fps resulting in a more conservative margin of error.
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PAOLINO and ZAMPA
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PAOLINO and ZAMPA
F I G U R E 8 Kinovea—­At the end of the
tracking, it is possible to read the average
speed of the vehicle from one frame to
another. [Colour figure can be viewed at
wileyonlinelibrary.com]
3
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R E S U LT S A N D D I S CU S S I O N
No significant differences were observed among the three cameras in relation to the angle view and the frame rate.
Table 1 summaries the results obtained at each speed.
Given these results, preliminary tests were conducted under two
As can be seen, the calculated vehicle speed is very similar to
casework scenarios, basically focused on a lower resolution and/or
Scout Speed radar system on every speed analysis section for the
frame rate (not variable) and higher level of compression. Table 2
constant speeds considered. The comparison of Scout reference
summaries the outcomes.
speed and calculated average vehicle speed by means of Kinovea
As expected, under casework conditions, the margin of error in-
found an average difference in 0.43 km/h, with a margin of error of
creases (± 2.07 km/h), but the speed calculation by means of Kinovea
±0.64 km/h.
is still reliable when compared to the ground truth.
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672
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TA B L E 1 Measured average speed and error rate
Canon XF405–­25 fps
JVC GY-­HM750E -­ 25 fps
JVC GS-­TD1BE –­ 29.97 fps
Actual
speed
(km/h)
Actual
speed
(km/h)
Actual
speed
(km/h)
Measured
average
speed (km/h)
Error rate %
Measured
average
speed (km/h)
27.21
Error rate %
27
27.15
0.56
27
28
28.04
0.14
28
47
47.66
1.40
47
48
47.67
−0.69
48
67
67.93
1.39
67
67
67.06
0.09
67
67.83
86
86.84
0.98
86
86.17
86
85.87
−0.15
86
86.35
0.41
105
106.25
1.19
105
104.95
−0.05
105
105.51
0.49
105
106.23
1.17
105
Measured
average
speed (km/h)
Error rate %
0.78
27
27.49
1.81
28.78
2.79
28
27.95
−0.18
46.67
−0.70
47
47.81
1.72
48.13
0.27
48
47.54
−0.96
67.2
0.30
67
67.93
1.01
1.24
67
66.87
−0.19
0.20
86
86.88
1.02
86
86.26
0.30
105
106.64
1.56
106.05
1.00
Calculated
speed range
(km/h)
26.2–­29.7
45.2–­51.3
64.2–­72.7
82.7–­93.8
100.2–­114.2
TA B L E 2 Lower resolution scenarios: Measured average speed and error rate
Canon XF405
LowerRes #1
LowerRes #2
Resolution (pixel)
768 × 432
Resolution (pixel)
768 × 432
Compression
H.264
Compression
H.264
fps
25
fps
10
Actual
speed
(km/h)
Measured
average speed
(km/h)
Error rate %
Calculated speed
range (km/h)
Actual
speed
(km/h)
Measured
average speed
(km/h)
Error rate %
Calculated speed
range (km/h)
27
27.96
3.56
25.4–­3 0.8
27
28.1
4.07
23.9–­32.9
47
48.13
2.40
43.2–­53.2
47
48.1
2.34
37.4–­54.1
67
68.03
1.54
62.4–­76.0
67
67.62
0.93
61.2–­86.2
87.73
2.01
79.5–­97.0
86
1.77
69.0–­97.5
106.54
1.47
97.2–­119.8
105
0.67
83.7–­121.6
86
105
87.52
105.7
It is important to observe that the as the frame rate of the re-
a. Four reference points for the calibration on the captured images
cording device decreases, the uncertainty measurement increases.
from videos. These points constitute a rectangle/square and real
The same happens when the speed of the vehicle increases.
distances must be known by the forensic examiner;
Despite the obtained results are promising, it is mandatory to
b. A specific element of the vehicle must stand on the same plane
note that further tests need to be conducted in order to verify how
of the above-­mentioned rectangle/square. This specific element
much lower resolutions and frame rates, as well as higher level of
needs to be visible in all the considered frames for the calculation
compression and camera to distance relationships would affect the
of the vehicle speed.
accuracy.
In order to validate the software, professional cameras were
4
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CO N C LU S I O N S
used at first. A driving test was performed under various driving
speeds and using different cameras at different viewing angles. The
vehicle speed was calculated by applying Kinovea to the videos, and
In the analysis of traffic accidents, forensic videos are an impor-
the estimated vehicle speeds were compared with an appropriately
tant source of proof. Different types of information can be ex-
calibrated speed radar system that was installed in the test vehi-
tracted, the speed of the vehicle at collision being one of the most
cle. In the test ground condition, the error values were in a range of
important.
0.14%–­2.79% under the constant speed condition.
This article suggests the use of the open-­source software
Further preliminary tests were conducted in order to verify if
Kinovea to estimate the speed of a vehicle videos captured by sta-
lower resolution and frame rate, as well as higher level of compres-
tionary cameras. Two requirements are needed to use this tool:
sion affected the measurements. The results are really encouraging.
15564029, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/1556-4029.15191 by Universidad Nacional Autonoma De Mexico, Wiley Online Library on [15/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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PAOLINO and ZAMPA
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PAOLINO and ZAMPA
The speed calculation remains reliable when compared to the
ground truth. As expected, the margin of error increases (range of
error values: 0.67%–­4.07%). Given that often the order of magnitude of speed is the core interest of the investigators, it is easy to
understand the Kinovea demonstrated to be a useful tool.
However, it is mandatory to note that further tests need to be
conducted in order to address the applicability of the measurement
technique with true CCTV/surveillance video recordings.
In any case, when the necessary requirements are satisfied,
Kinovea represents an easy and reliable (open source) tool and may
be of benefit to the forensic video examiners as it can efficiently
estimate the speed of vehicle in recorded digital video.
AC K N OW L E D G M E N T S
The authors wish to thank the Local Police of Formigine (Modena—­
Italy) for their valuable assistance in carrying out the experiments,
and Dr. Federico Cervelli for his useful and constructive comments
during the revision of this paper. The authors thank also the anonymous reviewers whose comments/suggestions helped improve and
clarify this manuscript.
C O N FL I C T O F I N T E R E S T
The authors have no conflicts of interest to declare.
ORCID
Francesco Zampa
https://orcid.org/0000-0002-4284-2439
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Stratford-­Upon-­Avon: ITAI; 2003. p. 51–­61.
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How to cite this article: Paolino S, Zampa F. Determination of
vehicle speed from recorded video using the open-­source
software Kinovea. J Forensic Sci. 2023;68:667–675. https://
doi.org/10.1111/1556-4029.15191
15564029, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/1556-4029.15191 by Universidad Nacional Autonoma De Mexico, Wiley Online Library on [15/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
674
TA B L E A 1 (Continued)
APPENDIX 1
TA B L E A 1 Extracts of the ffprobe reports generated by the
Amped FIVE tool for each camera used in this work (the first
twenty frames are shown).
pkt_pts
pkt_pts_time
675
pkt_dts_time
pkt_duration_time
Camera Canon XF405
0
0.000000
0.000000
0.040000
1
0.040000
0.040000
0.040000
2
0.080000
0.080000
0.040000
3
0.120000
0.120000
0.040000
4
0.160000
0.160000
0.040000
5
0.200000
0.200000
0.040000
6
0.240000
0.240000
0.040000
7
0.280000
0.280000
0.040000
8
0.320000
0.320000
0.040000
9
0.360000
0.360000
0.040000
10
0.400000
0.400000
0.040000
11
0.440000
0.440000
0.040000
12
0.480000
0.480000
0.040000
13
0.520000
0.520000
0.040000
14
0.560000
0.560000
0.040000
15
0.600000
0.600000
0.040000
16
0.640000
0.640000
0.040000
17
0.680000
0.680000
0.040000
18
0.720000
0.720000
0.040000
19
0.760000
0.760000
0.040000
20
0.800000
0.800000
0.040000
Camera JVC GY-­HM750E
0
0.000000
0.000000
0.040000
1
0.040000
0.040000
0.040000
2
0.080000
0.080000
0.040000
3
0.120000
0.120000
0.040000
4
0.160000
0.160000
0.040000
5
0.200000
0.200000
0.040000
6
0.240000
0.240000
0.040000
7
0.280000
0.280000
0.040000
8
0.320000
0.320000
0.040000
9
0.360000
0.360000
0.040000
10
0.400000
0.400000
0.040000
11
0.440000
0.440000
0.040000
12
0.480000
0.480000
0.040000
13
0.520000
0.520000
0.040000
14
0.560000
0.560000
0.040000
15
0.600000
0.600000
0.040000
16
0.640000
0.640000
0.040000
17
0.680000
0.680000
0.040000
18
0.720000
0.720000
0.040000
pkt_pts
pkt_pts_time
pkt_dts_time
pkt_duration_time
19
0.760000
0.760000
0.040000
20
0.800000
0.800000
0.040000
Camera JVC GS-­TD1BE
0
0.000000
0.000000
0.033367
1
0.033367
0.033367
0.033367
2
0.066733
0.066733
0.033367
3
0.100100
0.100100
0.033367
4
0.133467
0.133467
0.033367
5
0.166833
0.166833
0.033367
6
0.200200
0.200200
0.033367
7
0.233567
0.233567
0.033367
8
0.266933
0.266933
0.033367
9
0.300300
0.300300
0.033367
10
0.333667
0.333667
0.033367
11
0.367033
0.367033
0.033367
12
0.400400
0.400400
0.033367
13
0.433767
0.433767
0.033367
14
0.467133
0.467133
0.033367
15
0.500500
0.500500
0.033367
16
0.533867
0.533867
0.033367
17
0.567233
0.567233
0.033367
18
0.600600
0.600600
0.033367
19
0.633967
0.633967
0.033367
20
0.667333
0.667333
0.033367
15564029, 2023, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/1556-4029.15191 by Universidad Nacional Autonoma De Mexico, Wiley Online Library on [15/02/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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PAOLINO and ZAMPA