Implementations described herein relate to methods, systems, and computer-readable media to render a foreground video. In some implementations, a method includes receiving a plurality of video frames that include depth data and color data. The method further includes downsampling the frames of the video. The method further includes, for each frame, generating an initial segmentation mask that categorizes each pixel of the frame as foreground pixel or background pixel. The method further includes determining a trimap that classifies each pixel of the frame as known background, known foreground, or unknown. The method further includes, for each pixel that is classified as unknown, calculating and storing a weight in a weight map. The method further includes performing fine segmentation to obtain a binary mask for each frame. The method further includes upsampling the plurality of frames based on the binary mask for each frame to obtain a foreground video.

Aspects of the present disclosure provide an image-based face detection and recognition system that processes and/or analyzes portions of an image using image strips and cascading classifiers to detect faces and/or various facial features, such an eye, nose, mouth, cheekbone, jaw line, etc.

Techniques for identifying an emotional response and/or emotional state for a user in response to the user interacting with content may be described herein. For example, a series of facial images of a user may be captured by a user device and transmitted to a service computer that analyzes the images to identify changes in facial animation parameters. An emotional state and/or response may be determined by the service computer by utilizing the change in the facial animation parameters and a facial action coding system. In embodiments, the service computer may edit subsequent content prior to transmitting the content to the user device, utilize a particular communication channel to communicate the content, or identify a workflow that indicates a series of actions and/or content to be presented to the user device based on the determined emotional state/response of the user.

A system is provided for object localization in image data. The system includes an object localization framework comprising a plurality of object localization processes. The system is configured to receive an image comprising unannotated image data having at least one object in the image, access a first object localization process of the plurality of object localization processes, determine first bounding box information for the image using the first object localization process, wherein the first bounding box information comprises at least one first bounding box annotating at least a first portion of the at least one object in the image, and receive first feedback regarding the first bounding box information determined by the first object localization process. The system is further configured to persist the image with the first bounding box information or access a second object localization process based on the first feedback.

Aspects of the present disclosure provide an image-based face detection and recognition system that processes and/or analyzes portions of an image using image strips and cascading classifiers to detect faces and/or various facial features, such an eye, nose, mouth, cheekbone, jaw line, etc.

Systems and methods for self-determining optical inspection of wire bonds of semiconductor components. The method is an automated optical wire bond inspection method that may include obtaining an image of a semiconductor component having wire bonds. The method may also include detecting a plurality of wire bonds on the semiconductor component image so that a wire between at least two of the plurality of detected wire bonds may be detected. Further, the method may include determining an inspection region of interest corresponding to at least one detected wire bond and at least one detected wire. The method may then include inspecting the detected wire bond along the region of interest.

An active laser vision robust weld tracking system, a weld position detection method, and a robust weld tracking algorithm are disclosed in the present invention. The active laser vision robust weld tracking system comprises a laser source, a laser vision sensor, an image processing system, an industrial robot, and an electrical control system. A laser stripe associated with weld profile information is recognized by the laser vision sensor through projecting structured light onto the surface of a weld, the weld feature information is extracted using an image processing method, the position of the weld is detected from the central line of the laser stripe, and then the intelligent tracking of the weld is achieved with a variety of control methods.

A method for generating semantic information may include obtain a scanning image. The scanning image may include a plurality of pixels representing an anatomical structure. The method may also include obtain a trained segmentation model. The method may further include determine a location probability distribution of the anatomical structure in the scanning image based on the trained segmentation model. The method may also include generate a segmentation result related to the anatomical structure based on the location probability distribution. The method may further include save the segmentation result into a tag of a digital imaging and communications in medicine (DICOM) file.

Machine vision methods and systems determine if an object within a work field has one or more predetermined features. Methods comprise capturing image data of the work field, applying a filter to the image data, in which the filter comprises an aspect corresponding to a presumed feature, and based at least in part on the applying, determining if the object has the presumed feature. Systems comprise a camera system configured to capture image data of the work field, and a controller communicatively coupled to the camera system and programmed to apply a filter to the image data, and based at least in part on applying the filter, determine if the object has the specific feature. Robotic installation methods and systems that utilize machine vision methods and systems also are disclosed.

Aspects of the disclosure relate to a dynamic distance estimation output platform that utilizes improved computer vision and perspective transformation techniques to determine vehicle proximities from video footage. A computing platform may receive, from a visible light camera located in a first vehicle, a video output showing a second vehicle that is in front of the first vehicle. The computing platform may determine a longitudinal distance between the first vehicle and the second vehicle by determining an orthogonal distance between a center-of-projection corresponding to the visible light camera, and an intersection of a backside plane of the second vehicle and ground below the second vehicle. The computing platform may send, to an autonomous vehicle control system, a distance estimation output corresponding to the longitudinal distance, which may cause the autonomous vehicle control system to perform vehicle control actions.