Microsoft Technology Licensing, LLC

Nokia Technologies Oy

Nokia Corporation

Juuso Gren

Tomi Sokeila

Mikko Muukki

Eero Tuulos

Samuli Wallius

Kai Jämsä

Tomi Marko Juhani Sokeila

Antti Peräkamppi

Lassi Ylä-Soininmäki

Martti Olavi Ilmoniemi

A mobile apparatus is described. When the mobile apparatus is in a locked state and a user is detected, the user is authenticated automatically on background using a primary biometric authentication method. In response to authenticating the user automatically on background, the locked state of the mobile apparatus is opened, and a screen relating to the locked state on a display is provided although the locked state has been opened.

Authenticating a user with a mobile apparatus

In one example, a plurality of image frames captured by a digital camera unit is received. It is determined that a condition is met that requires a switch between image capture states. In response, automatic adjustment of at least one image capture parameter without user input is enabled or disabled.

Automatic processing of automatic image capture parameter adjustment

A computer-implemented flash artifact removal apparatus is described. The apparatus has at least a memory storing a flash image depicting a person's face captured in the presence of a flash illumination, and a non-flash image depicting the person's face captured without flash illumination. A plurality of pixels in the flash image comprise artifacts as a result of flash light reflecting from one or more eyes of the person. The apparatus has a flash artifact removal component which corrects the flash image by replacing at least some of the plurality of pixels in the flash image with pixels computed from at least the non-flash image. The flash artifact removal component is configured to detect edges of features of the one or more eyes in the non-flash image and to detect the plurality of pixels to be replaced in the flash image on the basis of the detected edges.

Flash and non-flash images in flash artifact removal

A method for compressing images includes identifying a set of image blocks from a plurality of digital images. For each image block from the set, image features of the image block are extracted. The set of image blocks is sorted into an ordered sequence of image blocks based on an average image feature difference between sequentially sorted image blocks. The set of image blocks is compressed into compressed image data based on inter block correlations between image blocks in the ordered sequence.

Image compression

In various examples there is an image combiner comprising a memory storing two or more frames being images depicting the same scene; and at least one processor. The memory holds instructions executable by the processor to select at least one of the frames and designate it as a reference frame and to designate the other frames as target frames. The instructions align the target frames to the reference frame and compute an output image by combining the reference frame and the aligned target frames. The process of selecting the reference frame comprises any one or more of: local analysis of characteristics of the frames, face detection, smile detection, object detection, computing signal to noise ratio of individual frames, use of sensor data from at least one non-camera sensor.

Combining images aligned to reference frame

An apparatus is described. In an embodiment, the apparatus comprises an illumination unit configured to simultaneously illuminate a first portion of a scene with unstructured light and a second portion of the scene with structured light. The apparatus further comprises a digital image capture unit configured to capture at least one image frame of the illuminated scene.

Digital camera unit with simultaneous structured and unstructured illumination

An apparatus including an image sensor configured to capture an image and optics, wherein the image sensor and optics align along an optical axis; optical image stabilization circuitry configured to determine and apply a target optical adjustment to compensate during capture of an image, for movement of the optical axis as a consequence of detected movement of the apparatus; post-capture image stabilization circuitry configured to process the captured image using a residual optical adjustment to obtain a compensated captured image, wherein the residual optical adjustment depends upon a difference between a measured optical adjustment, achieved during capture of the image, and the determined target optical adjustment.

Apparatus, method and computer program for image stabilization

The user calls to the mobile device with a predetermined pattern. In one embodiment the predetermined pattern is coded on the duration of the unanswered calls and the duration between successive calls. The predetermined pattern may be time coded on the durations of successive calls. After detecting the predetermined pattern the mobile device answers the incoming call. The user may continue by identifying via the voice line, if that is required. The mobile device responds to commands provided via the voice line, for example by providing contact information as synthesized speech.

Remote control of a mobile device

The Figures illustrate an apparatus, method, computer program and apparatus wherein the method includes detecting an input; and in response to detecting the input, causing an image capturing apparatus to capture a plurality of images; wherein the image capturing apparatus is configured to have a first set of parameters to capture a first subset of the plurality of images such that the first subset of the plurality of images are configured for use with a first image processing algorithm and the image capturing apparatus is configured to have a second set of parameters to capture a second subset of the plurality of images such that the second subset of the plurality of images are configured for use with a second image processing algorithm.

Method, apparatus and computer program for capturing images with multiple image capture and image modification

Determining an amount of motion in a second frame of video with reference to a first frame of video. Adaptively predicting a cropping factor for the second frame in response to the determined amount of motion. The cropping factor specifies a portion of the second frame that is to be excluded from the second frame. The predicted cropping factor is adaptively changed for a successive plurality of frames by buffering the first frame to predict a desired cropping factor for the second frame, wherein the first frame occurs prior to the second frame.

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Kyröskoski, Finland

Juuso Gren