Abstract: A method for grouping data items in a mobile device is disclosed. In this method, a plurality of data items and a sound tag associated with each of the plurality of data items are stored, and the sound tag includes a sound feature extracted from an input sound indicative of an environmental context for the data item. Further, the method may include generating a new data item, receiving an environmental sound, generating a sound tag associated with the new data item by extracting a sound feature from the environmental sound, and grouping the new data item with at least one of the plurality of data items based on the sound tags associated with the new data item and the plurality of data items.

Abstract: Methods, apparatuses, systems, and computer-readable media for rejecting false positive detection and tracking of image objects are presented. According to one or more aspects, a computing device may implement embodiments of the invention to use the movement of the mobile device for distinguishing false positives from true movement of the mobile device depicted in the field of view of the camera. In one embodiment, the actual movement of the mobile device may be measured using multi-modal sensor data from inertial sensors such as accelerometers and gyroscopes. In another embodiment, the actual movement of the device is calculated using the global movement of the mobile phone with reference to other objects in the field of view of the camera.

Abstract: A method includes receiving an alarm sound including information related to an emergency event. The method also includes transmitting, to a server, identification information of the mobile device and the information. The method further includes receiving, from the server, an instruction for responding to the emergency event. The method further includes outputting the instruction.

Abstract: Methods, apparatuses, systems, and computer-readable media for rejecting false positive detection and tracking of image objects are presented. According to one or more aspects, a computing device may implement embodiments of the invention to use the movement of the mobile device for distinguishing false positives from true movement of the mobile device depicted in the field of view of the camera. In one embodiment, the actual movement of the mobile device may be measured using multi-modal sensor data from inertial sensors such as accelerometers and gyroscopes. In another embodiment, the actual movement of the device is calculated using the global movement of the mobile phone with reference to other objects in the field of view of the camera.

Abstract: A method for controlling an application in a mobile device is disclosed. The method includes receiving environmental information, inferring an environmental context from the environmental information, and controlling activation of the application based on a set of reference models associated with the inferred environmental context. In addition, the method may include receiving a sound input, extracting a sound feature from the sound input, transmitting the sound feature to a server configured to group a plurality of mobile devices into at least one similar context group, and receiving, from the server, information on a leader device or a non-leader device and the at least one similar context group.

Abstract: A method for responding in an augmented reality (AR) application of a mobile device to an external sound is disclosed. The mobile device detects a target. A virtual object is initiated in the AR application. Further, the external sound is received, by at least one sound sensor of the mobile device, from a sound source. Geometric information between the sound source and the target is determined, and at least one response for the virtual object to perform in the AR application is generated based on the geometric information.

Abstract: Embodiments of the invention describe methods and apparatus for performing context-sensitive OCR. A device obtains an image using a camera coupled to the device. The device identifies a portion of the image comprising a graphical object. The device infers a context associated with the image and selects a group of graphical objects based on the context associated with the image. Improved OCR results are generated using the group of graphical objects. Input from various sensors including microphone, GPS, and camera, along with user inputs including voice, touch, and user usage patterns may be used in inferring the user context and selecting dictionaries that are most relevant to the inferred contexts.

Abstract: A method for processing a multi-channel image is disclosed. The method includes generating a plurality of grayscale images from the multi-channel image. At least one text region is identified in the plurality of grayscale images and text region information is determined from the at least one text region. The method generates text information of the multi-channel image based on the text region information. If the at least one text region includes a plurality of text regions, text region information from the plurality of text regions is merged to generate the text information. The plurality of the grayscale images is processed in parallel. In identifying the at least one text region, at least one candidate text region may be identified in the plurality of grayscale images and the at least one text region may be identified in the identified candidate text region.

Abstract: A method for recognizing a text block in an object is disclosed. The text block includes a set of characters. A plurality of images of the object are captured and received. The object in the received images is then identified by extracting a pattern in one of the object images and comparing the extracted pattern with predetermined patterns. Further, a boundary of the object in each of the object images is detected and verified based on predetermined size information of the identified object. Text blocks in the object images are identified based on predetermined location information of the identified object. Interim sets of characters in the identified text blocks are generated based on format information of the identified object. Based on the interim sets of characters, a set of characters in the text block in the object is determined.