Abstract: Images may be captured from a plurality of cameras of an object moving along a path. Each of the cameras may be positioned at a respective identified location in three-dimensional space. Correspondence information for the plurality of images linking locations on different ones of the images may be determined. Linked locations may correspond to similar portions of the object captured by the cameras. A portion of the plurality of images may be presented on a display screen via a graphical user interface. The plurality of images may be grouped based on the correspondence information.

Abstract: A plurality of images may be analyzed to determine an object model. The object model may have a plurality of components, and each of the images may correspond with one or more of the components. Component condition information may be determined for one or more of the components based on the images. The component condition information may indicate damage incurred by the object portion corresponding with the component.

Abstract: Images of an object may be captured via a camera at a mobile computing device at different viewpoints. The images may be used to identify components of the object and to identify damage estimates estimating damage to some or all of the components. Capture coverage levels corresponding with the components may be determined, and then recording guidance may be provided for capturing additional images to increase the capture coverage levels.

Abstract: A plurality of images of an object may be processed. The plurality of images may comprise a first image having an annotation. The plurality of images may further comprise second images. The annotation may be absent from the second images. A placement of the annotation for the second images such that the annotation is configured to be included in the second images may be automatically determined. The second images may be caused to include the annotation in accordance with the determined placement. The annotated second images may be stored on a storage device.

Abstract: According to various embodiments, techniques and mechanisms are provided to enhance damage detection and assessment for objects such as vehicles. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting. The vehicle surface images may be captured from a variety of perspectives. Damage assessed is mapped to multiple views of a vehicle. In some embodiments, a damage likelihood score is generated and if the damage likelihood score reaches a threshold, a heatmap visual representation may be generated and included in one or more views to present the type, likelihood, and extent of damage.

Abstract: According to various embodiments, techniques and mechanisms are provided to enhance damage detection for objects such as vehicles. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting. The vehicle surface images may be captured from a variety of perspectives. Striped lighting capture may be implemented using gaps between uniform lighting panels and the uniform lighting panels themselves, along with high speed cameras capable of taking more than 120 frames per second. The gap width between uniform lighting panels may be determined using an inverse relationship with frame rate. Damage may be determined using striped lighting illuminated vehicle surface images to identify the type, likelihood, and extent of damage.

Abstract: According to various embodiments, a variably switched striped lighting pattern panel is provided. A panel may include numerous rows of light emitting diodes (LEDs). Alternating rows are controlled separately by a microcontroller so that a first set can be switched on while a second set switched off to provide striped lighting. On the other hand, both sets can be switched on to provide for uniform lighting. Barriers may be provided between the rows of LEDs while a diffuser is placed in front of the LEDs. The variably switched striped lighting pattern panels can be used in a vehicle tunnel in a variety of configurations to allow for vehicle image capture in varying conditions for damage assessment.

Abstract: A computing system configured to process a plurality of intermediate outputs from machine learning models to generate final outputs may be maintained. A combined confidence metric that reflects a probability that the final outputs are accurate may be determined based on the intermediate outputs. Suitability of the combined outputs as inputs for a further model may be determined using the combined confidence metrics. The suitable combined outputs may be caused to be used as inputs for the further model.

Abstract: According to various embodiments, techniques and mechanisms are provided to enhance damage detection in vehicle tunnels. In some implementations, a semicylindrical striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting. The vehicle surface images may be captured from a variety of perspectives. The semicylindrical structure reduces edges and corners which can interfere with the generation of improved vehicle surface images illuminated with striped lighting. The vehicle surface images illuminated by striped lighting can be analyzed potentially with a vehicle object model. Damage may be determined using striped lighting illuminated vehicle surface images to identify the type, likelihood, and extent of damage.

Abstract: According to various embodiments, techniques and mechanisms are provided to improve striped lighting damage detection. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting and when illuminated by uniform panel lighting. The vehicle surface images may be captured from a variety of perspectives. The vehicle surface images can be analyzed to generate vehicle object models or can be analyzed by using these vehicle object models. Damage may be determined using the vehicle surface images to identify the type, likelihood, and extent of damage.

Abstract: According to various embodiments, techniques and mechanisms are provided to enhance damage detection for objects such as vehicles in vehicle tunnels. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting in a vehicle tunnel. Multiple vehicle surface images may be captured from a variety of perspectives. The vehicle surface images illuminated by striped lighting can be analyzed potentially with a vehicle object model. Each vehicle object model may include numerous object model components. Damage may be determined using striped lighting illuminated vehicle surface images to identify the type, likelihood, and extent of damage.

Abstract: Images may be captured from a plurality of cameras of an object moving along a path. Each of the cameras may be positioned at a respective identified location in three-dimensional space. Correspondence information for the plurality of images linking locations on different ones of the images may be determined. Linked locations may correspond to similar portions of the object captured by the cameras. A portion of the plurality of images may be presented on a display screen via a graphical user interface. The plurality of images may be grouped based on the correspondence information.

Abstract: A plurality of images may be analyzed to determine an object model. The object model may have a plurality of components, and each of the images may correspond with one or more of the components. Component condition information may be determined for one or more of the components based on the images. The component condition information may indicate damage incurred by the object portion corresponding with the component.

Abstract: A computing system configured to process a plurality of intermediate outputs from machine learning models to generate final outputs may be maintained. A combined confidence metric that reflects a probability that the final outputs are accurate may be determined based on the intermediate outputs. Outputs associated with combined confidence metrics that are below the threshold may be caused to be discarded.

Abstract: A computing system configured to process a plurality of intermediate outputs from machine learning models to generate final outputs may be maintained. A combined confidence metric that reflects a probability that the final outputs are accurate may be determined based on the intermediate outputs. A comprehensive damage assessment may be presented. The comprehensive damage assessment may include identified damage having combined confidence metrics determined to be above a threshold.

Abstract: A plurality of images of an object and a background may be captured. Three-dimensional representations of the background and the object may be generated based on the captured images. A synthetic image of the object and the background may be rendered. The synthetic image may depict a two-dimensional view of the object having a novel viewpoint different from the viewpoints of the captured images. A corrected synthetic image may be generated. The corrected synthetic image may be stored on a storage medium.

Abstract: A plurality of images of an object may be processed. The plurality of images may comprise a first image having an annotation. The plurality of images may further comprise second images. The annotation may be absent from the second images. A placement of the annotation for the second images such that the annotation is configured to be included in the second images may be automatically determined. The second images may be caused to include the annotation in accordance with the determined placement. The annotated second images may be stored on a storage device.

Abstract: A plurality of images of an object and a background may be captured. Three-dimensional representations of the background and the object may be generated based on the captured images. A synthetic image of the object and the background may be rendered. The synthetic image may depict a two-dimensional view of the object having a novel viewpoint different from the viewpoints of the captured images. A corrected synthetic image may be generated. The corrected synthetic image may be stored on a storage medium.

Abstract: Provided are mechanisms and processes for scene-aware selection of filters and effects for visual digital media content. In one example, a digital media item is analyzed with a processor to identify one or more characteristics associated with the digital media item, where the characteristics include a physical object represented in the digital media item. Based on the identified characteristics, a digital media modification is selected from a plurality of digital media modifications for application to the digital media item. The digital media modification may then be provided for presentation in a user interface for selection by a user.

Abstract: A background scenery portion may be identified in each of a plurality of image sets of an object, where each image set includes images captured simultaneously from different cameras. A correspondence between the image sets may determined, where the correspondence tracks control points associated with the object and present in multiple images. A multi-view interactive digital media representation of the object that is navigable in one or more dimensions and that includes the image sets may be generated and stored.