Abstract: The present disclosure generally relates to a system of a delivery device for combining sensor data from various types of sensors to generate a map that enables the delivery device to navigate from a first location to a second location to deliver an item to the second location. The system obtains data from RGB, LIDAR, and depth sensors and combines this sensor data according to various algorithms to detect objects in an environment of the delivery device, generate point cloud and pose information associated with the detected objects, and generates object boundary data for the detected objects. The system further identifies object states for the detected object and generates the map for the environment based on the detected object, the generated object proposal data, the labeled point cloud data, and the object states. The generated map may be provided to other systems to navigate the delivery device.

Abstract: Methods and systems are described for registering a sports field to a video. Video of a live event may feature participants at a venue. A template of the venue, including virtual markings that represent real markings on the venue, may be obtained. A homographic transformation between an image plane and a ground plane may be determined by matching virtual markings to corresponding real markings captured in at least one frame of the video. The determined homographic transformation may be used in the automated analysis of sports statistics and in improving inserted annotations and visualizations.

Abstract: Methods and systems are described for registering a sports field to a video. Video of a live event may feature participants at a venue. A template of the venue, including virtual markings that represent real markings on the venue, may be obtained. A homographic transformation between an image plane and a ground plane may be determined by matching virtual markings to corresponding real markings captured in at least one frame of the video. The determined homographic transformation may be used in the automated analysis of sports statistics and in improving inserted annotations and visualizations.

Abstract: Techniques for automatic scene change detection in a video are described. As one example, a computer-implemented method includes extracting features of a query shot and its neighboring shots of a first set of shots without labels with a query model, determining a key shot of the neighboring shots which is most similar to the query shot based at least in part on the features of the query shot and its neighboring shots, extracting features of the key shot with a key model, training the query model into a trained query model based at least in part on a comparison of the features of the query shot and the features of the key shot, extracting features of a second set of shots with labels with the trained query model, and training a temporal model into a trained temporal model based at least in part on the features extracted from the second set of shots and the labels of the second set of shots.

Abstract: Methods and systems are described for registering a sports field to a video. Video of a live event may feature participants at a venue. A template of the venue, including virtual markings that represent real markings on the venue, may be obtained. A homographic transformation between an image plane and a ground plane may be determined by matching virtual markings to corresponding real markings captured in at least one frame of the video. The determined homographic transformation may be used in the automated analysis of sports statistics and in improving inserted annotations and visualizations.

Abstract: Techniques for a comic book feature are described herein. A visual data stream of a video may be parsed into a plurality of frames. Scene boundaries may be determined to generate a scene using the plurality of frames where a scene includes a subset of frames. A key frame may be determined for the scene using the subset of frames. An audio portion of an audio data stream of the video may be identified that maps to the subset of frames based on time information. The key frame may be converted to a comic image based on an algorithm. First dimensions and placement for a data object may be determined for the comic image. The data object may include the audio portion for the comic image. A comic panel may be generated for the comic image that incorporates the data object using the determined first dimensions and the placement.

Abstract: Methods and systems are described for registering a sports field to a video. Video of a live event may feature participants at a venue. A template of the venue, including virtual markings that represent real markings on the venue, may be obtained. A homographic transformation between an image plane and a ground plane may be determined by matching virtual markings to corresponding real markings captured in at least one frame of the video. The determined homographic transformation may be used in the automated analysis of sports statistics and in improving inserted annotations and visualizations.

Abstract: Methods and systems are described for registering a sports field to a video. Video of a live event may feature participants at a venue. A template of the venue, including virtual markings that represent real markings on the venue, may be obtained. A homographic transformation between an image plane and a ground plane may be determined by matching virtual markings to corresponding real markings captured in at least one frame of the video. The determined homographic transformation may be used in the automated analysis of sports statistics and in improving inserted annotations and visualizations.

Abstract: The present disclosure generally relates to a system of a delivery device for combining sensor data from various types of sensors to generate a map that enables the delivery device to navigate from a first location to a second location to deliver an item to the second location. The system obtains data from RGB, LIDAR, and depth sensors and combines this sensor data according to various algorithms to detect objects in an environment of the delivery device, generate point cloud and pose information associated with the detected objects, and generates object boundary data for the detected objects. The system further identifies object states for the detected object and generates the map for the environment based on the detected object, the generated object proposal data, the labeled point cloud data, and the object states. The generated map may be provided to other systems to navigate the delivery device.

Abstract: An autonomous delivery robot system to enable delivery of a product to a customer is described. One autonomous ground vehicle (AGV) includes a processing device that receives a delivery request comprising a route divided into multiple navigation segments and computes a navigable space from perception data stored in a perception map. The perception map is a robot-centered local map that stores the perception data indicative of the surroundings of the AGV. The processing device computes a cost inflation from the perception data stored in the perception map, determines a sub-goal that is on the navigable space and reachable by the AGV using the navigable space and the cost inflation, and determines a path to achieve the sub-goal using the using the navigable space and the cost inflation. The processing device controls one or more actuators to move along the path.