Abstract:
Aspects of the disclosure relate generally to notifying a pedestrian of the intent of a self-driving vehicle. For example, the vehicle may include sensors which detect an object such as a pedestrian attempting or about to cross the roadway in front of the vehicle. The vehicle's computer may then determine the correct way to respond to the pedestrian. For example, the computer may determine that the vehicle should stop or slow down, yield, or stop if it is safe to do so. The vehicle may then provide a notification to the pedestrian of what the vehicle is going to or is currently doing. For example, the vehicle may include a physical signaling device, an electronic sign or lights, a speaker for providing audible notifications, etc.
Abstract:
Methods and systems for generating video from panoramic images using transition trees are provided. According to an embodiment, a method for generating a video from panoramic images may include receiving a transition tree corresponding to a current panoramic image from a server. The method may also include determining a path of the transition tree to a next panoramic image based on a user navigation request. The method may further include requesting and receiving a video chunk from the server for each edge of the determined path of the transition tree. The method may also include displaying the requested video chunks in sequence according to the transition tree. According to another embodiment, a system for generating a video from panoramic images may include a transition tree module and a video display module.
Abstract:
Example methods and systems for detecting weather conditions including wet surfaces using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle. The method also includes determining laser data points that are associated with one or more objects in the environment, and based on laser data points being unassociated with the one or more objects in the environment, identifying an indication that a surface on which the vehicle travels is wet. The method may further include receiving radar data collected for the environment of the vehicle that is indicative of a presence of the one or more objects in the environment of the vehicle, and identifying the indication that the surface on which the vehicle travels is wet further based on laser data points being unassociated with the one or more objects in the environment indicated by the radar data.
Abstract:
The present invention relates to annotating images. In an embodiment, the present invention enables users to create annotations corresponding to three-dimensional objects while viewing two-dimensional images. In one embodiment, this is achieved by projecting a selecting object onto a three-dimensional model created from a plurality of two-dimensional images. The selecting object is input by a user while viewing a first image corresponding to a portion of the three-dimensional model. A location corresponding to the projection on the three-dimensional model is determined, and content entered by the user while viewing the first image is associated with the location. The content is stored together with the location information to form an annotation. The annotation can be retrieved and displayed together with other images corresponding to the location.
Abstract:
Example methods and systems for detecting weather conditions using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle, and the laser data includes a plurality of laser data points. The method also includes associating, by a computing device, laser data points of the plurality of laser data points with one or more objects in the environment, and determining given laser data points of the plurality of laser data points that are unassociated with the one or more objects in the environment as being representative of an untracked object. The method also includes based on one or more untracked objects being determined, identifying by the computing device an indication of a weather condition of the environment.
Abstract:
A system and method of displaying transitions between street level images is provided. In one aspect, the system and method creates a plurality of polygons that are both textured with images from a 2D street level image and associated with 3D positions, where the 3D positions correspond with the 3D positions of the objects contained in the image. These polygons, in turn, are rendered from different perspectives to convey the appearance of moving among the objects contained in the original image.
Abstract:
A system and method include scanning a light detection and ranging (LIDAR) device through a range of orientations corresponding to a scanning zone while emitting light pulses from the LIDAR device. The method also includes receiving returning light pulses corresponding to the light pulses emitted from the LIDAR device and determining initial point cloud data based on time delays between emitting the light pulses and receiving the corresponding returning light pulses and the orientations of the LIDAR device. The initial point cloud data has an initial angular resolution. The method includes identifying, based on the initial point cloud data, a reflective feature in the scanning zone and determining an enhancement region and an enhanced angular resolution for a subsequent scan to provide a higher spatial resolution in at least a portion of subsequent point cloud data from the subsequent scan corresponding to the reflective feature.
Abstract:
Methods and systems for generating video from panoramic images using transition trees are provided. According to an embodiment, a method for generating a video from panoramic images may include receiving a transition tree corresponding to a current panoramic image from a server. The method may also include determining a path of the transition tree to a next panoramic image based on a user navigation request. The method may further include requesting and receiving a video chunk from the server for each edge of the determined path of the transition tree. The method may also include displaying the requested video chunks in sequence according to the transition tree. According to another embodiment, a system for generating a video from panoramic images may include a transition tree module and a video display module.
Abstract:
Methods and systems for object detection using multiple sensors are described herein. In an example embodiment, a vehicle's computing device may receive sensor data frames indicative of an environment at different rates from multiple sensors. Based on a first frame from a first sensor indicative of the environment at a first time period and a portion of a first frame that corresponds to the first time period from a second sensor, the computing device may estimate parameters of objects in the vehicle's environment. The computing device may modify the parameters in response to receiving subsequent frames or subsequent portions of frame of sensor data from the sensors even if the frames arrive at the computing device out of order. The computing device may provide the parameters of the objects to systems of the vehicle for object detection and obstacle avoidance.
Abstract:
Methods and systems for object detection using multiple sensors are described herein. In an example embodiment, a vehicle's computing device may receive sensor data frames indicative of an environment at different rates from multiple sensors. Based on a first frame from a first sensor indicative of the environment at a first time period and a portion of a first frame that corresponds to the first time period from a second sensor, the computing device may estimate parameters of objects in the vehicle's environment. The computing device may modify the parameters in response to receiving subsequent frames or subsequent portions of frame of sensor data from the sensors even if the frames arrive at the computing device out of order. The computing device may provide the parameters of the objects to systems of the vehicle for object detection and obstacle avoidance.