Axis

In an aspect, there is provided a method for performing digital image stabilization (DIS) on a sequence of video frames captured by an image capturing device, comprising: obtaining a sequence of motion values sampled from a motion signal while capturing the sequence of video frames such that each video frame is associated with a respective motion value; obtaining a sequence of position values sampled from a position signal while capturing the sequence of video frames such that each video frame is associated with a respective position value; determining, for each respective video frame, a residual motion value to obtain a sequence of residual motion values for the sequence of video frames; and performing DIS on the sequence of video frames, comprising: detecting an image feature in a reference video frame of the sequence of video frames; tracking the image feature in each further video frame of the sequence of video frames; determining frame motion data based on a displacement for the image feature in each further video frame in the sequence of video frames; and generating a stabilized sequence of video frames based on the frame motion data; wherein a size of a tracking window for tracking the image feature in each further video frame is set based on the sequence of residual motion values.

A computer-implemented method (1000) for tampering detection of a microphone device (100), the microphone device (100) comprising a microphone (110) arranged in a cavity (120) open to surroundings of the microphone device (110) via a microphone hole (122), the method (1000) comprising: receiving (1100) an audio signal (112) from the microphone (110); sampling (1200) the audio signal (112) for a low frequency band; detecting (1300) an event (140) comprising an exponentially decreasing absolute amplitude of the sampled audio signal (130) during a time period (P) of at least one second; and when detecting the event (140), outputting (1400) a tampering detection signal.

Provided is a device (100), and method as implemented by the device, for configuring a visual appearance of output images (123) from a camera (120) capturing a scene. The device is configured to obtain a first image (121) depicting the scene captured by the camera; obtain a second image (122) depicting the scene (as modified e.g. by a user using an image manipulation/creation software 140); extract a set of one or more visual differences between the first and second images, and determine, based on the extracted set of visual differences, one or more postprocessing operations, such that a third image (123) depicting the scene captured by the camera and subjected to the one or more image postprocessing operations is more visually equal (or similar) to the second image than the first image. A corresponding system, computer program and computer program product are also provided.

In an aspect there is provided a method for controlling an image stabilization, system of an image capturing device, wherein the IS system comprises an optical image stabilization, OIS, system compensating for vibrational movement of the image capturing device based on a motion signal output by a motion sensor of the image capturing device, and wherein the OIS system has at least a first control parameter with a value being adjustable to adapt a responsiveness of the OIS system to vibrational movement, the value being adjustable between a first value causing a lower responsiveness of the OIS system, and a second value causing a higher responsiveness of the OIS system; the method comprising, while the OIS system is in an active state and performs OIS; determining a signal-to-noise estimate for the motion signal; and determining the value of the first control parameter based on the signal-to-noise estimate, comprising setting the first control parameter to the first value responsive to determining that the signal-to-noise estimate is in a lower range, and to the second value responsive to determining that the signal-to-noise estimate is in an upper range.

This disclosure relates to methods 400, software, devices and systems for video scrubbing that enables a client device to retrieve images for scrubbing based on a user-requested time along a video timeline of a video stored in a server. The client device checks S404 if a cached image meets specified conditions, including a timestamp within a precision margin around the requested time. The precision margin scales with the timeline length, providing a smaller margin for shorter timelines and a larger margin for longer timelines. If a relevant cached image is found, it is retrieved S416; if not, an image with a highest relevance score within the precision margin is fetched S418 from the server and stored in memory.

In an aspect there is provided a method for controlling an OIS system of an image capturing device, the method comprising: obtaining a first and a second time-series of samples derived from a motion signal of a motion sensor of the image capturing device, wherein the motion signal indicates a motion of the image capturing device, and wherein the first time-series spans a longer time period of the motion signal than the second time-series; determining a current dominant frequency for the motion signal based on a frequency analysis of the first time-series; and determining a setpoint for the OIS system by: fitting to the second time-series a model function based on a sine and/or cosine function and the current dominant frequency, extrapolating the fitted model function past a last sample of the second time-series to predict a successive sample, and determining the setpoint based on the predicted successive sample.

A method (300) for streaming live coded video to one or more clients is disclosed. The method comprises: detecting (S302) a plurality of video stream requests; obtaining (S304) maximum bitrate values that return video streams are allowed to have; calculating (S306) requested quality of experience, QoE, values; determining (S308) a number of return video streams being lower than the plurality of video stream requests, and having bitrates such that each of the video stream requests can be matched with a return video stream, wherein the bitrates of the return video streams are determined such that a cumulative difference between the QoE value of each video stream request and a calculated return QoE of a matching return video stream is minimized; obtaining (S312) the return video streams; and streaming (S314) the return video streams. A streaming controller (20) for controlling streaming of live coded video is also disclosed.

The present disclosure relates to a computer-implemented method (100) for segmentation and/or object detection in images captured by a camera (201) having zoom capability, the method comprising: obtaining one or more images from the camera (201) (101); obtaining a zoom factor of the camera (201), wherein the zoom factor represents a measure of a current zoom level applied by the camera (201) when capturing the one or more images (102); selecting, based on the zoom factor, one neural network (204) from a plurality of neural networks (204) configured to segment the one or more images and/or detect one or more objects (206) in the one or more images, wherein the plurality of neural networks (204) are configured to operate at different image resolutions (103), wherein a higher zoom factor corresponds to selecting a neural network (204) configured to operate at a lower image resolution, and a lower zoom factor corresponds to selecting a neural network (204) configured to operate at a higher image resolution; down-scaling the one or more images to the image resolution required by the selected neural network (204) (104); applying the selected neural network (204) to segment the down-scaled one or more images and/or detect the one or more objects (206) in the down-scaled one or more images (105). The disclosure further relates to a corresponding camera system (200).

The present relates to a computer-implemented method to adjust a process noise of an object tracker in a camera (100) configured to monitor a scene (200) including moving objects (102a-c), the object tracker (107) uses a motion model (134) associated with process noise (132), the method comprising: determining (S100), using the object tracker, object tracks (136, 202a-c, 204a-b, 301) of moving objects travelling along a path in the scene for a time period using a level of process noise, evaluating (S105) at least one spatial parameter of the determined object tracks in relation to a predetermined criterion (140), repeating the steps of determining (S100) object tracks and evaluating (S105) at least one spatial parameter for object tracks during subsequent time periods using increased process noise for each iteration until the predetermined criterion is fulfilled or a maximum process noise limit is reached, and storing (S110) data (144) indicating the final process noise.

A method (500) for intra refresh encoding of a video stream is provided. The method includes encoding (S510) the video stream using a first intra refresh pattern; determining (S520) that a time-variation of bits-per-frame for encoding the video stream using a second intra refresh pattern different from the first intra refresh pattern is lower than that for encoding the video stream using the first intra refresh pattern, and switching (S530) to encoding the video stream using the second intra refresh pattern. A corresponding device configured to perform the method is also provided, as well as a corresponding computer program and computer program product.