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.

Abstract: A device, and method of signing a video segment comprising one or more groups of pictures, GOPs, wherein each GOP comprises a header and one or more frames, are disclosed. For each of the one or more GOPs a GOP hash is produced and the GOP hash is digitally signed by means of a digital signature to produce a signed GOP hash. For each GOP except a last GOP of the one or more GOPs the respective signed GOP hash is saved in the header of a subsequent GOP. An additional GOP is added to the video segment after the last GOP of the one or more GOPs, wherein the additional GOP comprising a header and one or more frames. The signed GOP hash of the last GOP of the one or more GOPs is saved in the header of the additional GOP.

Abstract: Systems, methods and non-transitory computer-readable media transform raw image data into a video stream comprising a plurality of encoded image frames. To reduce memory bandwidth and power consumption, compression rates of sets of imaging data temporarily stored in memory during the transformation of raw image data into the video stream are adapted based on encoding configurations, on a pixel block level.

Abstract: A method includes detecting a first object in a first area of a scene; determining, based on characteristics of the first object, a first probability value indicating a first probability that the detected first object; detecting a second object in a second area of the scene captured in a second stream of image frames by a second camera of the camera system different from the first camera, wherein the second area at least partly overlaps the first area; determining, based on characteristics of the second object, a second probability value indicating a second probability that the detected second object; and when the second probability value is below a second threshold value and the first probability value is above a first threshold value determining an updated second probability value by increasing the second probability value.

Abstract: A thermometric camera for determining a temperature of an object in motion comprises a bolometer sensor and circuitry. The bolometer sensor captures a sequence of image frames of the object while the object is moving. The circuitry executes: an object identifying function configured to identify an area corresponding to the object in each image frame of a series of image frames among the sequence of image frames; a combining function configured to combine the identified areas from each image frame in the series of image frames into a stacked image of the object, wherein pixel values in the stacked image of the object are estimated as a sum of pixel values of the corresponding pixels in the image frames in the series of image frames; and a temperature determining function configured to determine the temperature of the object in motion from pixel values in the stacked image of the object.

Abstract: A method for defining an outline of a region in an image having distorted lines comprises displaying a first image version having distorted lines, wherein lines in a first image portion of the first version have a reduced distortion, receiving user input defining a first outline portion of the outline of region in the first version, wherein the first outline portion includes one or more lines in the first image portion of the first version, displaying a further version of the image having distorted lines, wherein lines in a further image portion of the further version have a reduced distortion, and receiving user input defining a further outline portion of the outline of the region in the further, wherein the further outline portion includes one or more lines in the further portion of the further version.

Abstract: A method of enabling a remote access to a first network device from a second network device includes the second device generating a data item signed by a network service trusted by the first device, and including a fingerprint of a public key of the second device. The signed data item is sent to the first device via a signalling service, SIGS, as part of a negotiation of terms for a peer-to-peer connection. The first device uses the received signed data item to verify that the terms it receives from the SIGS has not been tampered with by the SIGS, in order to prevent the SIGS from performing a Man-In-The-Middle attack. Various network devices and a network system are also provided.

Abstract: A method detects one or more occluded areas of a scene analysed by an object tracking system. The method includes building a map of one or more occluded areas in a scene. Building the map comprises running a re-identification algorithm on a video sequence to try to resume a lost object track. If the object track is successfully resumed, the method includes determining an area of the scene where the first object track is lost and an area of the scene where the first object track is resumed. A connection between the first and the second area of the scene is added the map such that the map identifies that an object track being lost in the first area of the scene has been resumed in the second area of the scene.

Abstract: A method for determining images plausible to have a false negative object detection comprises providing a group of historic trajectories, wherein each historic trajectory comprises a reference track that represents one or more historic tracks and comprises an object class of historic object detections that belong to the one or more historic tracks; performing tracking; performing object detection; for a determined track that does not match any determined object detection, comparing the determined track with reference tracks of historic trajectories for identifying a matching reference track; upon identifying a matching reference track, defining images of the determined track as being plausible to have a false negative object detection for the object class of the historic trajectory comprising the matching reference track; and upon not identifying a matching reference track, defining the determined track as a false positive track.