Stationary and Moving Camera Video Analysis Compared to Known Reference System

Simacek, Daniel; Tovar, Jose M. Castillo; Famiglietti, Nicholas; Shkolkin, Vladimir; Hoang, Ryan

doi:10.4271/2021-01-0879

Cited by 3 publications

References 4 publications

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Reconstruction of the Motion of Traffic Accident Vehicle in the Vehicle‐Mounted Video Based on Direct Linear Transform

Feng,

Chen,

Heng

2024

Journal of Advanced Transportation

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Based on the principle of direct linear transformation (DLT) in close‐range photogrammetry, a method was proposed for reconstructing the motion states of the host vehicle and other vehicles based on vehicle‐mounted videos. To verify the effectiveness and accuracy of the method, validation experiments were designed. Under two typical operating states, steering and straight driving, the motion states of the host vehicle and other vehicles (including trajectory, distance, speed, and acceleration) were reconstructed from the vehicle‐mounted video. In the experiments, high‐precision inertial navigation was installed on the other vehicle to record real‐time motion data of the vehicle. Finally, in order to compare and analyze the reconstructed video results with the vehicle’s actual motion data, the recorded motion data were matched and synchronized to the same time axis as the vehicle‐mounted videos through a GPS timing device. The experimental result shows that the reconstructed trajectory results based on this method can generally reflect the vehicle’s actual trajectory, with an average deviation of less than 7.4%; the reconstructed distance results have an average deviation of less than 9.3%; the reconstructed speed results have an average deviation of less than 7.3%; the reconstructed acceleration results can reflect the vehicle’s acceleration or deceleration states. The results of this study provide an effective solution for obtaining important parameters of vehicles in accident reconstruction research, such as the trajectory, speed, distance, and acceleration or deceleration, and it has significant practical value for applications.

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Reconstruction of the Motion of Traffic Accident Vehicle in the Vehicle‐Mounted Video Based on Direct Linear Transform

Feng,

Chen,

Heng

2024

Journal of Advanced Transportation

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Evaluation of Tesla Dashcam Video System for Speed Determination Via Reverse Projection Photogrammetry

Molnar¹,

Peck²

2023

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">Recent Tesla models contain four integrated onboard cameras that serve the Autopilot and Self-Driving Capabilities of the vehicle and act as a dashcam by recording footage to a local USB drive. The purpose of this study is to analyze the footage recorded by the integrated cameras and determine its suitability for speed determinations of both the host vehicle and surrounding vehicles through photogrammetry analyses. The front and rear cameras of the test vehicle (2019 Tesla Model 3) were calibrated for focal length and lens distortion characteristics. Two types of tests were performed to determine host vehicle speed: constant-speed and acceleration. Several frames from each test were analyzed. The distance between camera locations was used to gather vehicle speed through a time distance analysis. These speeds were compared to those gathered via the onboard GPS instrumentation. Two additional types of tests were performed to determine surrounding vehicle speeds: a vehicle approaching from the rear and an offset vehicle approaching from the front. For both tests, the Tesla was stationary. Several frames from each test were analyzed via reverse projection, using a point cloud of the approaching vehicles. The speeds obtained through photogrammetry were compared to GPS instrumentation onboard the approaching vehicle. The mean difference between photogrammetry and GPS instrumentation ranged between 0.38 and 0.72 mph across all tests.</div></div>

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Uncertainty Introduced by Image Projection in Video-Based Reconstructions of Vehicle Positions and Speeds

Young,

Flynn,

Miller

et al. 2024

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">Video evidence in collision reconstruction has become a common foundation for vehicle position and speed analyses. The goal of this study was to explore how the uncertainty of these position/speed analyses is affected by various camera-, scene-, and vehicle-related properties. To achieve this goal, we quantified how the size and aspect ratio of pixels in the pixel grid change as a result of correcting for lens distortion and projecting the pixel grid onto a real-world surface captured by the image. Relying on both general and case-specific examples, we used Monte Carlo analyses to explore how uncertainty can be calculated and how it varies for different measurements and different camera-, scene-, and vehicle-related properties. We found that i) the aspect ratio of image pixels projected onto a road surface can vary by multiple orders of magnitude over an entire image and generally increases rapidly as the projected pixel nears the horizon; ii) the uncertainty associated with the real-world position of an object in an image depends on the measurement direction in relation to the elongated axis of the projected pixels in the region of interest, and iii) physical kinematic constraints that govern the motion of a vehicle can be used to reduce the uncertainty of a pixel-based analysis in some situations. Overall, these findings show that uncertainty in video-based reconstruction analyses cannot be expressed as a universally applicable percent error; instead, the uncertainty of a measurement depends on the unique combination of camera, scene, and vehicle in a specific analysis.</div></div>

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Stationary and Moving Camera Video Analysis Compared to Known Reference System

Cited by 3 publications

References 4 publications

Reconstruction of the Motion of Traffic Accident Vehicle in the Vehicle‐Mounted Video Based on Direct Linear Transform

Reconstruction of the Motion of Traffic Accident Vehicle in the Vehicle‐Mounted Video Based on Direct Linear Transform

Evaluation of Tesla Dashcam Video System for Speed Determination Via Reverse Projection Photogrammetry

Uncertainty Introduced by Image Projection in Video-Based Reconstructions of Vehicle Positions and Speeds

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