Abstract: Apparatus and methods related to photography are provided. A computing device can receive an input image. An object detector of the computing device can determine an object region of interest of the input image that is associated with an object detected in the input image. A trained machine learning algorithm can determine an output photographic region of interest for the input image based on the object region of interest and the input image. The machine learning algorithm can be trained to identify an output photographic region of interest that is suitable for use by a photographic function for image generation. The computing device can generate an output related to the output photographic region of interest.

Abstract: A method performed by an electronic device is described. The method includes obtaining a first frame of a scene. The method also includes performing object recognition of at least one object within a first bounding region of the first frame. The method further includes performing object tracking of the at least one object within the first bounding region of the first frame. The method additionally includes determining a second bounding region of a second frame based on the object tracking. The second frame is subsequent to the first frame. The method also includes determining whether the second bounding region is valid based on a predetermined object model.

Abstract: An apparatus includes an object detector configured to receive image data of a scene viewed from the apparatus and including an object. The image data is associated with multiple scale space representations of the scene. The object detector is configured to detect the object responsive to location data and a first scale space representation of the multiple scale space representations.

Abstract: A device includes a sensor configured to determine an angle of a longitudinal extent of the device with respect to a ground surface. The device also includes an estimator configured to estimate a first distance and to estimate a second distance based on the angle and the first distance. The first distance is associated with a first projection from a center of the device to the ground surface. The first projection is perpendicular to the longitudinal extent of the device. The second distance is associated with a second projection from the center of the device to the ground surface. The second projection is perpendicular to the ground surface.

Abstract: A system and method of object detection are disclosed. In a particular implementation, a method of processing an image includes receiving, at a processor, image data associated with an image of a scene. The scene includes a road region. The method further includes detecting the road region based on the image data and determining a subset of the image data. The subset excludes at least a portion of the image data corresponding to the road region. The method further includes performing an object detection operation on the subset of the image data to detect an object. The object detection operation performed on the subset of the image data is exclusive of the at least a portion of the image data corresponding to the road region.

Abstract: A method of processing data includes receiving, at a computing device, data representative of an image captured by an image sensor. The method also includes determining a first scene clarity score. The method further includes determining whether the first scene clarity score satisfies a threshold, and if the first scene clarity score satisfies the threshold, determining a second scene clarity score based on second data extracted from the data.

Abstract: A system and method of object detection are disclosed. In a particular implementation, a method of processing an image includes receiving, at a processor, image data associated with an image of a scene. The scene includes a road region. The method further includes detecting the road region based on the image data and determining a subset of the image data. The subset excludes at least a portion of the image data corresponding to the road region. The method further includes performing an object detection operation on the subset of the image data to detect an object. The object detection operation performed on the subset of the image data is exclusive of the at least a portion of the image data corresponding to the road region.

Abstract: The invention provides a robust method to control interactive media using gestures. A method to retrieve metadata information from a multimedia outlet device, wherein the method follows the steps: (1) extracting image hot spot areas in a current captured image using face detection, (2) detecting a human gesture directive in at least one image hot spot area using gesture recognition, (3) determining if the gesture directive matches a pre-assigned command to a rich interaction module, (4) sending a signal to a rich interaction module corresponding to the pre-assigned command detected, (5) extracting a media image hot spot area from electrical signals sent from the multimedia, (6) matching any detected human gestures in at least one image hot spot area using gesture recognition with a specific pixel on a device screen, and (7) retrieving information from metadata assigned to an area of pixels on the screen.

Abstract: A particular method includes determining, based on data received from at least one motion sensor, a movement of a mobile device from a first position to a second position. The method also includes computing a three-dimensional (3D) model of an object based on a first image of the object corresponding to a first view of the object from the first position of the mobile device, a second image of the object corresponding to a second view of the object from the second position of the mobile device, and the movement of the mobile device.

Abstract: Techniques and systems are provided for encoding video data. For example, a method of encoding video data includes obtaining a background picture that is generated based on a plurality of pictures captured by an image sensor. The background picture is generated to include background portions identified in each of the captured pictures. The method further includes encoding, into a video bitstream, a group of pictures captured by the image sensor. The group of pictures includes at least one random access picture. Encoding the group of pictures includes encoding at least a portion of the at least one random access picture using inter-prediction based on the background picture.

Abstract: A method performed by an electronic device is described. The method includes obtaining a first frame of a scene. The method also includes performing object recognition of at least one object within a first bounding region of the first frame. The method further includes performing object tracking of the at least one object within the first bounding region of the first frame. The method additionally includes determining a second bounding region of a second frame based on the object tracking. The second frame is subsequent to the first frame. The method also includes determining whether the second bounding region is valid based on a predetermined object model.

Abstract: A device includes a sensor configured to determine an angle of a longitudinal extent of the device with respect to a ground surface. The device also includes an estimator configured to estimate a first distance and to estimate a second distance based on the angle and the first distance. The first distance is associated with a first projection from a center of the device to the ground surface. The first projection is perpendicular to the longitudinal extent of the device. The second distance is associated with a second projection from the center of the device to the ground surface. The second projection is perpendicular to the ground surface.

Abstract: The disclosed technology relates to image-capturing methods. In one aspect, a method includes receiving an image frame comprising a plurality of pixels and subtracting foreground pixels from the image frame to obtain background pixels. The method additionally includes determining an exposure condition for a next image frame based on at least a subset of the background pixels. The method further includes adjusting the foreground pixels such that a difference between a background luma value and a foreground luma value of the next image frame is within a predetermined range. Aspects are also directed to apparatuses configured for the methods.

Abstract: In a particular embodiment, a method includes evaluating, at a mobile device, a first area of pixels to generate a first result. The method further includes evaluating, at the mobile device, a second area of pixels to generate a second result. Based on comparing a threshold with a difference between the first result and the second result, a determination is made that the second area of pixels corresponds to a background portion of a scene or a foreground portion of the scene.

Abstract: Methods and apparatus for capturing an image using an automatic focus are disclosed herein. In one aspect, a method is disclosed which includes communicating, using a camera, with a wireless device via a wireless communication network. The method further includes determining a distance between the camera and the wireless device using the wireless communication network and adjusting a focus of the camera based upon the determined distance. Finally, the method includes capturing an image using the adjusted focus of the camera. In some aspects, this method may be done on a smartphone or digital camera which includes Wi-Fi capabilities.

Abstract: A method of processing data includes receiving, at a computing device, data representative of an image captured by an image sensor. The method also includes determining a first scene clarity score. The method further includes determining whether the first scene clarity score satisfies a threshold, and if the first scene clarity score satisfies the threshold, determining a second scene clarity score based on second data extracted from the data.

Abstract: An apparatus includes an object detector configured to receive image data of a scene viewed from the apparatus and including an object. The image data is associated with multiple scale space representations of the scene. The object detector is configured to detect the object responsive to location data and a first scale space representation of the multiple scale space representations.

Abstract: Methods and apparatus for capturing an image using an automatic focus are disclosed herein. In one aspect, a method is disclosed which includes communicating, using a camera, with a wireless device via a wireless communication network. The method further includes determining a distance between the camera and the wireless device using the wireless communication network and adjusting a focus of the camera based upon the determined distance. Finally, the method includes capturing an image using the adjusted focus of the camera. In some aspects, this method may be done on a smartphone or digital camera which includes Wi-Fi capabilities.

Abstract: The disclosed technology relates to image-capturing methods. In one aspect, a method includes receiving an image frame comprising a plurality of pixels and subtracting foreground pixels from the image frame to obtain background pixels. The method additionally includes determining an exposure condition for a next image frame based on at least a subset of the background pixels. The method further includes adjusting the foreground pixels such that a difference between a background luma value and a foreground luma value of the next image frame is within a predetermined range. Aspects are also directed to apparatuses configured for the methods.

Abstract: Aspects of this disclosure are directed to techniques to store values indicative of one or more scissor regions in a scissor buffer. In aspects of this disclosure, a processor may receive two dimensional (2-D) coordinates of a scissor region. The processor may transform the 2-D coordinates into coordinates that include more than two dimensions. The processor may store a value indicative of the scissor region in one or more storage units of the scissor buffer based on the coordinates that include more than two dimensions.