Patent application number | Description | Published |
20120224715 | Noise Adaptive Beamforming for Microphone Arrays - The subject disclosure is directed towards a noise adaptive beamformer that dynamically selects between microphone array channels, based upon noise energy floor levels that are measured when no actual signal (e.g., no speech) is present. When speech (or a similar desired signal) is detected, the beamformer selects which microphone signal to use in signal processing, e.g., corresponding to the lowest noise channel. Multiple channels may be selected, with their signals combined. The beamformer transitions back to the noise measurement phase when the actual signal is no longer detected, so that the beamformer dynamically adapts as noise levels change, including on a per-microphone basis, to account for microphone hardware differences, changing noise sources, and individual microphone deterioration. | 09-06-2012 |
20120268369 | Depth Camera-Based Relative Gesture Detection - The subject disclosure is directed towards using timing and/or relative depth data to reduce false positives in gesture detection within a depth-sensed region. Depth camera data is processed to position a cursor over a displayed representation of a control. If the user's hand hovers over the control for a threshold time period, and then changes hand depth a relative amount (e.g., pushes the hand forward a delta amount), an event is fired. The displayed representation of the control may change (e.g., enlarge) upon hovering. The relative depth may be computed based upon the depth when the user hand initially enters the control area. The relative depth may remain the same if the user pulls the hand away from the camera by tracking the maximum depth and firing the event when the maximum depth value minus the current depth value reaches a delta value. | 10-25-2012 |
Patent application number | Description | Published |
20120316680 | TRACKING AND FOLLOWING OF MOVING OBJECTS BY A MOBILE ROBOT - A robot tracks objects using sensory data, and follows an object selected by a user. The object can be designated by a user from a set of objects recognized by the robot. The relative positions and orientations of the robot and object are determined. The position and orientation of the robot can be used so as to maintain a desired relationship between the object and the robot. Using the navigation system of the robot, during its movement, obstacles can be avoided. If the robot loses contact with the object being tracked, the robot can continue to navigate and search the environment until the object is reacquired. | 12-13-2012 |
20130016852 | SOUND SOURCE LOCALIZATION USING PHASE SPECTRUMAANM Regunathan; ShankarAACI RedmondAAST WAAACO USAAGP Regunathan; Shankar Redmond WA USAANM Koishida; KazuhitoAACI RedmondAAST WAAACO USAAGP Koishida; Kazuhito Redmond WA USAANM Kikkeri; Harshavardhana NarayanaAACI BellevueAAST WAAACO USAAGP Kikkeri; Harshavardhana Narayana Bellevue WA US - An array of microphones placed on a mobile robot provides multiple channels of audio signals. A received set of audio signals is called an audio segment, which is divided into multiple frames. A phase analysis is performed on a frame of the signals from each pair of microphones. If both microphones are in an active state during the frame, a candidate angle is generated for each such pair of microphones. The result is a list of candidate angles for the frame. This list is processed to select a final candidate angle for the frame. The list of candidate angles is tracked over time to assist in the process of selecting the final candidate angle for an audio segment. | 01-17-2013 |
20130342493 | Touch Detection on a Compound Curve Surface - Described is detecting touch on a compound curve surface that displays content for touch-based interaction. Touch may be detected by processing an infrared image to detect a shadow corresponding to the touch, and/or by detecting infrared reflection corresponding to the touch. Also described is providing a curved surface with capacitive sensing. Also described is the use of frustrated total internal reflection to detect touch. | 12-26-2013 |
20130342652 | TRACKING AND FOLLOWING PEOPLE WITH A MOBILE ROBOTIC DEVICE - Tracking and following technique embodiments are presented that are generally employed to track and follow a person using a mobile robotic device having a color video camera and a depth video camera. A computer associated with the mobile robotic device is used to perform various actions. Namely, in a tracking mode, a face detection method and the output from the color video camera is used to detect potential persons in an environment. In addition, a motion detection method and the output from the depth video camera is also used to detect potential persons in the environment. Detection results obtained using the face and motion detection methods are then fused and used to determine the location of one or more persons in the environment. Then, in a following mode, a mobile robotic device following method is used to follow a person whose location was determined in the tracking mode. | 12-26-2013 |
20130343600 | SELF LEARNING FACE RECOGNITION USING DEPTH BASED TRACKING FOR DATABASE GENERATION AND UPDATE - Face recognition training database generation technique embodiments are presented that generally involve collecting characterizations of a person's face that are captured over time and as the person moves through an environment, to create a training database of facial characterizations for that person. As the facial characterizations are captured over time, they are will represent the person's face as viewed from various angles and distances, different resolutions, and under different environmental conditions (e.g., lighting and haze conditions). Further, over a long period of time where facial characterizations of a person are collected periodically, these characterizations can represent an evolution in the appearance of the person. This produces a rich training resource for use in face recognition systems. In addition, since a person's face recognition training database can be established before it is needed by a face recognition system, once employed, the training will be quicker. | 12-26-2013 |
20150092986 | FACE RECOGNITION USING DEPTH BASED TRACKING - Face recognition training database generation technique embodiments are presented that generally involve collecting characterizations of a person's face that are captured over time and as the person moves through an environment, to create a training database of facial characterizations for that person. As the facial characterizations are captured over time, they are will represent the person's face as viewed from various angles and distances, different resolutions, and under different environmental conditions (e.g., lighting and haze conditions). Further, over a long period of time where facial characterizations of a person are collected periodically, these characterizations can represent an evolution in the appearance of the person. This produces a rich training resource for use in face recognition systems. In addition, since a person's face recognition training database can be established before it is needed by a face recognition system, once employed, the training will be quicker. | 04-02-2015 |