Abstract: A method for encoding a video stream includes obtaining images of a scene captured by a camera at a first resolution; identifying regions of interest (ROIs) in an image; adding, as part of an encoded video stream, a first video frame encoding at least part of the image at a second resolution lower than the first resolution; adding a second video frame marked as a no-display frame, and being an inter-frame referencing the first video frame with motion vectors for upscaling of the ROIs; adding a third video frame encoding the ROIs at a third resolution higher than the second resolution, and being an inter-frame referencing the second video frame.

Abstract: An image processing device generates an output image with masking of objects of classes. An input image is downscaled to an object detection image having a lower resolution than the input image and lower than the output image. The object detection image is input to an object detection module and confidence scores for pixel areas are received from the object detection module. Each confidence score indicates a probability that the pixel area relates to an object to be masked. Based on the input image, an intermediate image is generated having a higher resolution than the object detection image resolution and an adaptive masking threshold is set such that the greater the ratio between the output image resolution and the object detection image resolution, the lower the masking threshold. The output image is then generated by masking pixel areas of the intermediate image.

Abstract: A method of encoding images in a video, comprises: acquiring an original image from an image sensor of a video camera; encoding the original image using a generative image model, thereby obtaining a first encoded image; decoding the image to obtain a first decoded image; identify a region of interest (ROI) of the original image; for each ROI: perform an encoding quality check by comparing several reference points in the ROI of the original image against corresponding reference points in the ROI of the first decoded image, thereby obtaining a difference; if the difference is greater than a threshold, encoding the ROI using a non-generative image model, thereby obtaining a non-generative encoded image area; providing final encoded image data comprising a) the non-generative encoded image areas for the ROI having a difference greater than the threshold and b) the first encoded image for a remaining part of the original image.

Abstract: A method for selecting a crop score threshold for enhancing tracking of objects in a scene captured in a video sequence is disclosed. A respective track is obtained for two different objects, each track comprising crops of object instances of the objects in in a video sequence, each crop having a crop score and a feature vector. Each track is split into respective more tracklets thereby forming four or more tracklets. For each candidate crop score threshold a respective difference between each tracklet and each other tracklet is determined based on differences between feature vectors of crops having a crop score above the candidate crop score threshold of each tracklet, and each other tracklet. A crop score threshold is selected from the set of crop score thresholds resulting in a maximum difference between the differences between tracklets of different tracks and the differences between tracklets of the same track.

Abstract: A method for classifying a detected object is disclosed. First and second object detectors detect first and second objects in first and second image frames, respectively, of a video sequence, and first and second probability scores respectively are calculated indicating a probability that the detected object belongs to a specific class. The second image frame is subsequent to the first image frame. The first object detector has a higher object detection precision and a longer processing time than the second object detector. The first and second object detections are performed in parallel. Reducing the first classification threshold or increasing the first probability score are performed if the first probability score is below a first classification threshold and the second probability score is above a second classification threshold. The first object is determined to belong to the specific class based on the probability scores and the classification thresholds.

Abstract: A method of generating an output video stream is provided, including receiving a first input video stream from at least one first camera capturing a scene, receiving a second input video stream from a second camera only partially capturing the scene, and generating an output video stream from the first input video stream, including, in response to determining that a particular area of the output video stream depicts a part of the scene depicted in the second input video stream, refraining from, or at least reducing a level of, a masking of the particular area of the output video stream. A corresponding device, camera monitoring system, computer program and computer program product are also provided.

Abstract: A method for classifying tracks in radar detections of a scene acquired by a stationary radar unit, comprises: acquiring radar detections of the scene using the static radar unit; feeding at least a portion of the radar detections into a tracker module for producing track-specific feature data indicating a specific track in the scene, feeding at least a portion of the radar detections into a scene model comprising information about scene-specific features aggregated over time, and information indicating areas in the scene with expected ghost target detections and areas with expected real target detections, wherein at least a subset of the scene-specific features is determined from the radar detections; classifying the specific track as belonging to a real target or to a ghost target by relating the specific track to a position in the scene model.

Abstract: Upon detecting an event indicating enabling of security sensitive functionality of an electronic device, a value previously unknown to the electronic device is obtained and the current content of the data storage to a new current content of the data storage is updated according to an updating function based on the current content of the data storage and the value, wherein, without privileged access, the current content of the data storage can only be updated using the updating function. The value is further obtained in a management module and an expected new current content of the data storage is determined in the management module according to the updating function based on known original content of the data storage and the value. Upon determining that the new current content of the data storage differs from the expected new current content of the data storage, a validation module generates a security notification.

Abstract: The present disclosure generally relates to the field of camera surveillance, and in particular to a method and control unit for controlling a bitrate of a video stream captured with an image acquisition device.

Abstract: A computer implemented method for controlling a transmission of a video stream is provided. The method comprises estimating a number of bits for a group of pictures, GOP, of the video stream to be transmitted, setting a latency requirement for the transmission of the video stream, determining an average minimum video bitrate across the GOP based on the estimated number of bits and a time corresponding to a time period represented by a duration of the GOP, for video frames in the GOP setting an output bitrate for transmission of a video frame based on the latency requirement and the average minimum video bitrate, and transmitting the video frame using the output bitrate.

Abstract: This disclosure relates to methods systems and non-transitory computer-readable storage mediums for distributing load in a multi-chip image processing unit for processing image data into processed image data. An example method comprises receiving first image data, analysing the first image data using a first algorithm, the first algorithm performing a set number of operations for a given size of image data input to the first algorithm, and outputs at least one characteristic of the first image data; using the at least one characteristic to estimate use of memory bandwidth in the first and second chip when processing the first image data into processed image data; and distributing processing of the first image data between the first and the second chip such that the estimated use of memory bandwidth is distributed evenly.

Abstract: A system for handling bandwidth shortage for transmission of encoded video frames. In a sending device, a long term reference frame which indicates bandwidth shortage is created. During a first time period, the reference frame is sent to the receiving device for storage. During a subsequent second time period, bandwidth shortage is determined in the sending device, wherein the bandwidth during the second time period is insufficient if the encoded video frames are encoded according to an encoding principle used at times without bandwidth shortage. During the second time period, inter encoded frames referencing the long term reference frame are sent, wherein each frame includes encoded blocks, and at least a subset of the blocks of the inter encoded frames are empty blocks such that the bit rate of the inter encoded frames is lower or equal to the bandwidth during the second time period.

Abstract: A method for processing of data by applying a first algorithm in a system comprising a server and a client device comprises at the client device: continuously receiving data; dividing the received data into M>1 subsets of data, each subset of data comprising, or being derived from, sensor data captured by a sensor during a capture time interval at a plurality of points in time; determining for each subset whether the processing of the subset should be performed by the client device or by the server, and upon determining that the processing should be performed by the client device, processing the subset into processed data by applying the first algorithm to the subset, and transmitting the processed data to the server, and upon determining that processing should be performed by the server, transmitting the subset of data to the server.

Abstract: A method for temperature calibration and determination of a temperature in a scene. At each time point out of a plurality of time points in a first period of time, collecting an ambient temperature representing a temperature at a first part of the scene and collecting thermal image sensor signal values corresponding to the collected ambient temperatures and relating to the first part. Determine a calibration function based on the collected ambient temperatures and the thermal image sensor signal values corresponding to each of the collected ambient temperatures. In a second period of time, capturing a thermal image of the scene comprising thermal image sensor signal values relating to a second part of the scene and determine a temperature at the second part of the scene based on the calibration function and based on thermal image sensor signal values comprised in the thermal image.

Abstract: A device and method merge a first candidate area relating to a candidate feature in a first image and a second candidate area relating to a candidate feature in a second image. The first and second images have an overlapping region, and at least a portion of the first and second candidate areas are located in the overlapping region. An image overlap size is determined indicating a size of the overlapping region of the first and second images, and a candidate area overlap ratio is determined indicating a ratio of overlap between the first and second candidate areas. A merging threshold is then determined based on the image overlap size, and, on condition that the candidate area overlap ratio is larger than the merging threshold, the first candidate area and the second candidate area are merged, thereby forming a merged candidate area.

Abstract: A method for stray light compensation is disclosed. The method comprising: acquiring a first image with a first imaging device covering a first field-of-view; acquiring a second image with a second imaging device covering a second field-of-view, wherein the second field-of-view is larger than the first field-of-view and wherein the first field-of-view is included in the second field-of-view; estimating stray light components in pixels of the first image from pixel data of pixels in the second image; and compensating for stray light in the first image by subtracting the estimated stray light components in pixels of the first image. Also, a system for stray light compensation is disclosed.

Abstract: A method for masking of objects in a video stream, the method comprising: acquiring a video stream; detecting an object in the video stream; determining whether the detected object belongs to a foreground of the video stream indicative of moving objects or to a background of the video stream indicative of static objects; classifying the detected object to be of a specific type using a first classifier if the detected object is determined to belong to the foreground, and using a second classifier if the detected object is determined to belong to the background, the first classifier being different from the second classifier, and if the detected object is classified as being of the specific type of object, masking the object in the video stream.