Abstract: A method of object detection includes receiving a first image taken from a first perspective by a first camera and receiving a second image taken from a second perspective, different from the first perspective, by a second camera. Each pixel in the first image is offset relative to a corresponding pixel in the second image by a predetermined offset distance resulting in offset first and second images. A particular pixel of the offset first image depicts a same object locus as a corresponding pixel in the offset second image only if the object locus is at an expected object-detection distance from the first and second cameras. The method includes recognizing that a target object is imaged by the particular pixel of the offset first image and the corresponding pixel of the offset second image.

Abstract: Implementations described and claimed herein provide systems and methods for interaction between a user and a machine. In one implementation, a system is provided that receives an input from a user of a mobile machine which indicates or describes an object in the world. In one example, the user may gesture to the object which is detected by a visual sensor. In another example, the user may verbally describe the object which is detected by an audio sensor. The system receiving the input may then determine which object near the location of the user that the user is indicating. Such a determination may include utilizing known objects near the geographic location of the user or the autonomous or mobile machine.

Abstract: Signals usable to determine a path of a vehicle towards a particular stopping point in a vicinity of a destination are detected from an individual authorized to provide guidance with respect to movements of the vehicle. Based at least in part on the signals and a data set pertaining to the external environment of the vehicle, one or more vehicular movements to be implemented to proceed along the path are identified. A directive is transmitted to a motion control subsystem of the vehicle to initiate one of the vehicular movements.

Abstract: Signals usable to determine a path of a vehicle towards a particular stopping point in a vicinity of a destination are detected from an individual authorized to provide guidance with respect to movements of the vehicle. Based at least in part on the signals and a data set pertaining to the external environment of the vehicle, one or more vehicular movements to be implemented to proceed along the path are identified. A directive is transmitted to a motion control subsystem of the vehicle to initiate one of the vehicular movements.

Abstract: A method of object detection includes receiving a first image taken from a first perspective by a first camera and receiving a second image taken from a second perspective, different from the first perspective, by a second camera. Each pixel in the first image is offset relative to a corresponding pixel in the second image by a predetermined offset distance resulting in offset first and second images. A particular pixel of the offset first image depicts a same object locus as a corresponding pixel in the offset second image only if the object locus is at an expected object-detection distance from the first and second cameras. The method includes recognizing that a target object is imaged by the particular pixel of the offset first image and the corresponding pixel of the offset second image.

Abstract: Signals usable to determine a path of a vehicle towards a particular stopping point in a vicinity of a destination are detected from an individual authorized to provide guidance with respect to movements of the vehicle. Based at least in part on the signals and a data set pertaining to the external environment of the vehicle, one or more vehicular movements to be implemented to proceed along the path are identified. A directive is transmitted to a motion control subsystem of the vehicle to initiate one of the vehicular movements.

Abstract: Various technologies described herein pertain to creation of an output hyper-lapse video from an input video. Values indicative of overlaps between pairs of frames in the input video are computed. A value indicative of an overlap between a pair of frames can be computed based on a sparse set of points from each of the frames in the pair. Moreover, a subset of the frames from the input video are selected based on the values of the overlaps between the pairs of the frames in the input video and a target frame speed-up rate. Further, the output hyper-lapse video is generated based on the subset of the frames. The output hyper-lapse video can be generated without a remainder of the frames of the input video other than the subset of the frames.

Abstract: A “Stroke Untangler” composes handwritten messages from handwritten strokes representing overlapping letters or partial letter segments are drawn on a touchscreen device or touch-sensitive surface. These overlapping strokes are automatically untangled and then segmented and combined into one or more letters, words, or phrases. Advantageously, segmentation and composition is performed without requiring user gestures, timeouts, or other inputs to delimit characters within words, and without using handwriting recognition-based techniques to guide untangling and composing of the overlapping strokes to form characters. In other words, the user draws multiple overlapping strokes. Those strokes are then automatically segmented and combined into one or more corresponding characters. Text recognition of the resulting characters is then performed. Further, the segmentation and combination is performed in real-time, thereby enabling real-time rendering of the resulting characters in a user interface window.

Abstract: A method of object detection includes receiving a first image taken by a first stereo camera, receiving a second image taken by a second stereo camera, and offsetting the first image relative to the second image by an offset distance selected such that each corresponding pixel of offset first and second images depict a same object locus if the object locus is at an assumed distance from the first and second stereo cameras. The method further includes locating a target object in the offset first and second images.

Abstract: Implementations described and claimed herein provide systems and methods for interaction between a user and a machine. In one implementation, a system is provided that receives an input from a user of a mobile machine which indicates or describes an object in the world. In one example, the user may gesture to the object which is detected by a visual sensor. In another example, the user may verbally describe the object which is detected by an audio sensor. The system receiving the input may then determine which object near the location of the user that the user is indicating. Such a determination may include utilizing known objects near the geographic location of the user or the autonomous or mobile machine.

Abstract: A first set of signals corresponding to a first signal modality (such as the direction of a gaze) during a time interval is collected from an individual. A second set of signals corresponding to a different signal modality (such as hand-pointing gestures made by the individual) is also collected. In response to a command, where the command does not identify a particular object to which the command is directed, the first and second set of signals is used to identify candidate objects of interest, and an operation associated with a selected object from the candidates is performed.

Abstract: The description relates to a smart ring. In one example, the smart ring can be configured to be worn on a first segment of a finger of a user. The example smart ring can include at least one flexion sensor secured to the smart ring in a manner that can detect a distance between the at least one flexion sensor and a second segment of the finger. The example smart ring can also include an input component configured to analyze signals from the at least one flexion sensor to detect a pose of the finger.

Abstract: A “Stroke Untangler” composes handwritten messages from handwritten strokes representing overlapping letters or partial letter segments are drawn on a touchscreen device or touch-sensitive surface. These overlapping strokes are automatically untangled and then segmented and combined into one or more letters, words, or phrases. Advantageously, segmentation and composition is performed without requiring user gestures, timeouts, or other inputs to delimit characters within words, and without using handwriting recognition-based techniques to guide untangling and composing of the overlapping strokes to form characters. In other words, the user draws multiple overlapping strokes. Those strokes are then automatically segmented and combined into one or more corresponding characters. Text recognition of the resulting characters is then performed. Further, the segmentation and combination is performed in real-time, thereby enabling real-time rendering of the resulting characters in a user interface window.

Abstract: Described is a technology by which an image such as a stitched panorama is automatically cropped based upon predicted quality data with respect to filling missing pixels. The image may be completed, including by completing only those missing pixels that remain after cropping. Predicting quality data may be based on using restricted search spaces corresponding to the missing pixels. The crop is computed based upon the quality data, in which the crop is biased towards including original pixels and excluding predicted low quality pixels. Missing pixels are completed by using restricted search spaces to find replacement values for the missing pixels, and may use histogram matching for texture synthesis.

Abstract: Technologies pertaining to composing, displaying, and/or transmitting handwritten content through utilization of a touch-sensitive display screen of a mobile computing device are described herein. A user of the mobile computing device can set forth strokes on the touch-sensitive display screen, one on top of another, wherein such strokes correspond to different handwritten characters. Stroke segmentation can be undertaken to determine which strokes correspond to which characters in a handwritten sequence of characters.

Abstract: Various technologies described herein pertain to creation of an output hyper-lapse video from an input video. Values indicative of overlaps between pairs of frames in the input video are computed. A value indicative of an overlap between a pair of frames can be computed based on a sparse set of points from each of the frames in the pair. Moreover, a subset of the frames from the input video are selected based on the values of the overlaps between the pairs of the frames in the input video and a target frame speed-up rate. Further, the output hyper-lapse video is generated based on the subset of the frames. The output hyper-lapse video can be generated without a remainder of the frames of the input video other than the subset of the frames.

Abstract: Various technologies described herein pertain to creation of an output hyper-lapse video from an input video. Values indicative of overlaps between pairs of frames in the input video are computed. A value indicative of an overlap between a pair of frames can be computed based on a sparse set of points from each of the frames in the pair. Moreover, a subset of the frames from the input video are selected based on the values of the overlaps between the pairs of the frames in the input video and a target frame speed-up rate. Further, the output hyper-lapse video is generated based on the subset of the frames. The output hyper-lapse video can be generated without a remainder of the frames of the input video other than the subset of the frames.

Abstract: The description relates to a smart ring. In one example, the smart ring can be configured to be worn on a first segment of a finger of a user. The example smart ring can include at least one flexion sensor secured to the smart ring in a manner that can detect a distance between the at least one flexion sensor and a second segment of the finger. The example smart ring can also include an input component configured to analyze signals from the at least one flexion sensor to detect a pose of the finger.

Abstract: The description relates to a smart ring. In one example, the smart ring can be configured to be worn on a first segment of a finger of a user. The example smart ring can include at least one flexion sensor secured to the smart ring in a manner that can detect a distance between the at least one flexion sensor and a second segment of the finger. The example smart ring can also include an input component configured to analyze signals from the at least one flexion sensor to detect a pose of the finger.

Abstract: Various technologies described herein pertain to creation of an output hyper-lapse video from an input video. Values indicative of overlaps between pairs of frames in the input video are computed. A value indicative of an overlap between a pair of frames can be computed based on a sparse set of points from each of the frames in the pair. Moreover, a subset of the frames from the input video are selected based on the values of the overlaps between the pairs of the frames in the input video and a target frame speed-up rate. Further, the output hyper-lapse video is generated based on the subset of the frames. The output hyper-lapse video can be generated without a remainder of the frames of the input video other than the subset of the frames.