Error Estimation for Known Marker Position Retrieval by Ideal Pinhole Camera Direct Observation

2016 ◽  
Vol 841 ◽  
pp. 192-197
Author(s):  
Constantin Radu Mirescu ◽  
Gabriela Roșca
Keyword(s):  
Gait Analysis ◽  
Error Estimation ◽  
Motion Capture ◽  
Direct Observation ◽  
Focal Point ◽  
Pinhole Camera ◽  
Point Of View ◽  
Direct Approach ◽  
Marker Position

For Motion Capture in Gait Analysis using Known Spherical Markers one simple direct approach is to compute the projection of the Marker Center using its projection in the Pixel Plane and based on it to find the location of the Marker on the line that connects the Marker Center Projection and the camera Focal Point. For various positions of the Marker in the workspace the exact image of the marker is computed using a genuine approach and compute back the approximation of the position based on the generated image. Various algorithms are taken in consideration and finally the results are assessed from the point of view of Gait Analysis and two directions for calculus improvement are identified.

Estimate of Color Depth Discretization Impact on the Accuracy of an Ideal Pinhole Camera

2015 ◽  
Vol 811 ◽  
pp. 217-221
Author(s):  
Constantin Radu Mirescu ◽  
Gabriela Roșca
Keyword(s):  
Motion Capture ◽  
Final Analysis ◽  
Major Axis ◽  
Black Box ◽  
Pinhole Camera ◽  
Box Model ◽  
Marker Position ◽  
Single Location ◽  
Marker Location ◽  
Color Depth

This paper investigates the limits of precision caused by color depth discretization in motion capture with known sphere marker in a uniform lighted scene for an ideal pinhole camera using a black box model. For each marker position its ellipse projection in the pixel plane is computed and the final pixel values are established based on how match the pixel area is covered by the marker image. The color of some boundary pixels loses information due to the color depth discretization and therefore the same image represents a range of marker location in space and not a single location. The maximum variations on all the major axis are computed with a precision of 100 nm for each marker location and a final analysis is performed using this findings.

A Precise Algorithm for Known Spherical Marker Position Retrieval Using an Ideal Pinhole Camera in a Diffuse Light Scene

2016 ◽  
Vol 859 ◽  
pp. 93-98
Author(s):  
Constantin Radu Mirescu ◽  
Gabriela Roșca
Keyword(s):  
Focal Point ◽  
Pinhole Camera ◽  
Diffuse Light ◽  
Symmetry Center ◽  
Marker Position ◽  
Line Passing ◽  
The Right ◽  
Depth View

The exact marker image was computed for various positions in the workspace and for each image was computed back the approximation of the marker position based on it. The position computation used the symmetry of the scene and the particular characteristics of the ellipse marker projection. Was established that the center of symmetry of the marker projection is different than the projection of the marker center itself and the the relation between two was found using the Dandeline Spheres. For a given marker radius the ratio between the area of the right cone base that contains the marker center projection and the area of the marker projection was expressed as a law based only on the angle of the line passing through the focal point and the symmetry center of the marker projection and the view axis. Based on all these intermediary results was obtained an algorithm with a precision under 0.04 mm in sagital plane, and under 0.1 mm on the depth view axis with a modest 1920x1680 camera resolution.

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane

2022 ◽  
pp. 095441192110729
Author(s):  
Gunjan Patel ◽  
Rajani Mullerpatan ◽  
Bela Agarwal ◽  
Triveni Shetty ◽  
Rajdeep Ojha ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Motion Analysis ◽  
Motion Capture ◽  
Inertial Sensor ◽  
Joint Kinematics ◽  
Percentage Error ◽  
Motion Capture System ◽  
Spatiotemporal Parameters ◽  
Analysis System ◽  
Motion Capture Systems

Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor ( n = 15) and outdoor ( n = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson’s correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the “Good” category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups.

From observation to enactment: Can dance experience enhance multisensory temporal integration?

2012 ◽  
Vol 25 (0) ◽  
pp. 188
Author(s):  
Helena Sgouramani ◽  
Chris Muller ◽  
Leon van Noorden ◽  
Marc Leman ◽  
Argiro Vatakis
Keyword(s):  
Motion Capture ◽  
Temporal Integration ◽  
Stimulus Onset ◽  
Point Of View ◽  
Motion Capture System ◽  
Temporal Window ◽  
Synchronous Condition ◽  
First Time ◽  
Method Of Constant Stimuli

We report two experiments aiming to define how experience and stimulus enactment affect multisensory temporal integration for ecologically-valid stimuli. In both experiments, a number of different dance steps were used as audiovisual displays at a range of stimulus onset asynchronies using the method of constant stimuli. Participants were either professional dancers or non-dancers. In Experiment 1, using a simultaneity judgment (SJ) task, we aimed at defining — for the first time — the temporal window of integration (TWI) for dancers and non-dancers and the role of experience in SJ performance. Preliminary results showed that dancers had smaller TWI in comparison to non-dancers for all stimuli tested, with higher complexity (participant rated) dance steps requiring larger auditory leads for both participant groups. In Experiment 2, we adapted a more embodied point of view by examining how enactment of the stimulus modulates the TWIs. Participants were presented with simple audiovisual dance steps that could be synchronous or asynchronous and were asked to synchronize with the audiovisual display by actually performing the step indicated. A motion capture system recorded their performance at a millisecond level of accuracy. Based on the optimal integration hypothesis, we are currently looking at the data in terms of which modality will be dominant, considering that dance is a spatially (visual) and temporally (audio) coordinated action. Any corrective adjustments, accelerations–decelerations, hesitations will be interpreted as indicators of the perception of ambiguity in comparison to their performance at the synchronous condition, thus, for the first time, an implicit SJ response will be measured.

scholarly journals Human Gait-labeling Uncertainty and a Hybrid Model for Gait Segmentation

2021 ◽  
Author(s):  
Jiaen Wu ◽  
Henrik Maurenbrecher ◽  
Alessandro Schaer ◽  
Barna Becsek ◽  
Chris Awai Easthope ◽  
...  
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Ground Truth ◽  
Absolute Error ◽  
Human Gait ◽  
Heel Strike ◽  
Analysis Model ◽  
Flat Foot ◽  
Dynamic Time ◽  
Human Gait Analysis

<div><div><div><p>Motion capture systems are widely accepted as ground-truth for gait analysis and are used for the validation of other gait analysis systems.To date, their reliability and limitations in manual labeling of gait events have not been studied.</p><p><b>Objectives</b>: Evaluate human manual labeling uncertainty and introduce a new hybrid gait analysis model for long-term monitoring.</p><p><b>Methods</b>: Evaluate and estimate inter-labeler inconsistencies by computing the limits-of-agreement; develop a model based on dynamic time warping and convolutional neural network to identify a valid stride and eliminate non-stride data in walking inertial data collected by a wearable device; Gait events are detected within a valid stride region afterwards; This method makes the subsequent data computation more efficient and robust.</p><p><b>Results</b>: The limits of inter-labeler agreement for key</p><p>gait events of heel off, toe off, heel strike, and flat foot are 72 ms, 16 ms, 22 ms, and 80 ms, respectively; The hybrid model's classification accuracy for a stride and a non-stride are 95.16% and 84.48%, respectively; The mean absolute error for detected heel off, toe off, heel strike, and flat foot are 24 ms, 5 ms, 9 ms, and 13 ms, respectively.</p><p><b>Conclusions</b>: The results show the inherent label uncertainty and the limits of human gait labeling of motion capture data; The proposed hybrid-model's performance is comparable to that of human labelers and it is a valid model to reliably detect strides in human gait data.</p><p><b>Significance</b>: This work establishes the foundation for fully automated human gait analysis systems with performances comparable to human-labelers.</p></div></div></div>

Michael Haneke: Glaciation, Legitimacy and Transgression

2018 ◽  
pp. 139-162
Author(s):  
Simon Hobbs
Keyword(s):  
Focal Point ◽  
Point Of View ◽  
Art Cinema ◽  
The Way

This chapter examines the extreme cinema of Michael Haneke. Whilst increasingly well covered in scholarly accounts of extreme art cinema, Haneke’s work is most often approached from an aesthetic and thematic point of view, wherein the text becomes the focal point. While these studies are key to understanding Haneke’s films, and the metaphorical significance he places on scenes of brutalism and sex, it has left certain areas underexplored. This chapter addresses this by undertaking detailed paratextual analysis of Haneke’s key extreme films. Firstly, the chapter focuses upon Funny Games, the most critically disliked Haneke film. Looking first at Tartan Video’s release before discussing Artificial Eye’s remediation, the chapter highlights the important role time can play in defining the commercial validity of extremity. Showing how the growing status of Haneke’s auteur brand challenged the use extreme iconography, the chapter alludes to the ways highbrow commercial symbols compete with lowbrow traits. Thereafter, the chapter undertakes an assessment of Artificial Eye’s ‘Michael Haneke Trilogy’. This example – due the centralisation of a dead pig on the cover – exposes the way paratexts can oppose critical and cultural canonisation.

Wearable Kinesthetic System for Joint Knee Flexion-Extension Monitoring In Gait Analysis

2011 ◽  
pp. 792-800
Author(s):  
Mario Tesconi ◽  
Enzo Pasquale Scilingo ◽  
Pierluigi Barba ◽  
Danilo De Rossi
Keyword(s):  
Gait Analysis ◽  
Subjective Experience ◽  
Neuromuscular Diseases ◽  
Medical Personnel ◽  
Quantitative Information ◽  
Point Of View ◽  
Clinical Environment ◽  
Patient Status ◽  
Main Challenge ◽  
Movement Ability

Posture and motion of body segments are the result of a mutual interaction of several physiological systems such as nervous, muscle-skeletal, and sensorial. Patients who suffer from neuromuscular diseases have great difficulties in moving and walking, therefore motion or gait analysis are widely considered matter of investigation by the clinicians for diagnostic purposes. By means of specific performance tests, it could be possible to identify the severity of a neuromuscular pathology and outline possible rehabilitation planes. The main challenge is to quantify a motion anomaly, rather than to identify it during the test. At first, visual inspection of a video showing motion or walking activity is the simplest mode of examining movement ability in the clinical environment. It allows us to collect qualitative and bidimensional data, but it does not provide neither quantitative information about motion performance modalities (for instance about dynamics and muscle activity), nor about its changes. Moreover, the interpretation of recorded motion pattern is demanded to medical personnel who make a diagnosis on the basis of subjective experience and expertise. A considerable improvement in this analysis is given by a technical contribution to quantitatively analyse body posture and gesture. Advanced technologies allow us to investigate on anatomic segments from biomechanics and kinematics point of view, providing a wide set of quantitative variables to be used in multi-factorial motion analysis. A personal computer enables a realtime 3D reconstruction of motion and digitalizes data for storage and off-line elaboration. For this reason, the clinicians have a detailed description of the patient status and they can choose a specific rehabilitation path and verify the subject progress.

Wearable Kinesthetic System for Joint Knee Flexion-Extension Monitoring In Gait Analysis

2008 ◽  
pp. 1390-1397
Author(s):  
Mario Tesconi ◽  
Enzo Pasquale Scilingo ◽  
Pierluigi Barba ◽  
Danilo De Rossi
Keyword(s):  
Gait Analysis ◽  
Subjective Experience ◽  
Neuromuscular Diseases ◽  
Medical Personnel ◽  
Quantitative Information ◽  
Point Of View ◽  
Clinical Environment ◽  
Patient Status ◽  
Main Challenge ◽  
Movement Ability

Posture and motion of body segments are the result of a mutual interaction of several physiological systems such as nervous, muscle-skeletal, and sensorial. Patients who suffer from neuromuscular diseases have great difficulties in moving and walking, therefore motion or gait analysis are widely considered matter of investigation by the clinicians for diagnostic purposes. By means of specific performance tests, it could be possible to identify the severity of a neuromuscular pathology and outline possible rehabilitation planes. The main challenge is to quantify a motion anomaly, rather than to identify it during the test. At first, visual inspection of a video showing motion or walking activity is the simplest mode of examining movement ability in the clinical environment. It allows us to collect qualitative and bidimensional data, but it does not provide neither quantitative information about motion performance modalities (for instance about dynamics and muscle activity), nor about its changes. Moreover, the interpretation of recorded motion pattern is demanded to medical personnel who make a diagnosis on the basis of subjective experience and expertise. A considerable improvement in this analysis is given by a technical contribution to quantitatively analyse body posture and gesture. Advanced technologies allow us to investigate on anatomic segments from biomechanics and kinematics point of view, providing a wide set of quantitative variables to be used in multi-factorial motion analysis. A personal computer enables a realtime 3D reconstruction of motion and digitalizes data for storage and off-line elaboration. For this reason, the clinicians have a detailed description of the patient status and they can choose a specific rehabilitation path and verify the subject progress.

Sign in / Sign up

Export Citation Format

Share Document