Abstract: A method for thermal image processing, comprises: acquiring a thermal image depicting a scene; obtaining a frequency distribution based on pixel intensities of the thermal image; processing the frequency distribution to determine whether the frequency distribution comprises a peak, caused by a hot object in the scene, which is separated from a thermal background of the scene by more than an intensity threshold; and in response to determining that the frequency distribution comprises the peak, processing the thermal image to suppress a ghost image of the hot object in the thermal image, wherein the ghost image is caused by internal reflections of radiation from the hot object in the thermal camera, and wherein the processing of the thermal image comprises: estimating a location of ghost image pixels forming the ghost image; and suppressing the ghost image in the thermal image by adjusting intensities of the ghost image pixels.

Abstract: A method of processing digital video data comprises continuously capturing digital video data representing image frames. While capturing the digital video data, the digital video data is encoded into a sequence of encoded image frames, the sequence comprising key frames and delta frames, and storing the sequence of encoded image frames. It is then determined that the stored sequence of encoded image frames is to be entropy coded and, as a consequence, entropy coding the sequence of encoded image frames into an entropy coded sequence of image frames and storing the entropy coded sequence of image frames.

Abstract: The present system and method generally relate to the field of camera surveillance, and in particular to object re-identification in video streams captured by a camera.

Abstract: A method, system and software for determine a color of a tracked object. Using a first video sequence and foreground objects detected therein, a color rendering metric may be determined for each area of a plurality of areas in the scene. Such color rendering metrics may then be used in case a tracked object is determined to have different colors in different images of a second video sequence, such that the colors detected in an area associated with a higher color rendering metric is selected over an area associated with a lower color rendering metric.

Abstract: A method for adding at least one additional image frame to a stream of encoded image frames, the stream of encoded image frames comprising image frames encoded by an encoder. An event relating to at least one of: i) a change of operation state of a sender of the stream of encoded image frames, or ii) a change of connection state between the sender and a receiver is detected. Depending on the type of the detected event, the at least one additional image frame is provided. Each at least one additional image frame comprises a reference to a preceding image frame and codes a predetermined visual change relative to the preceding image frame. The predetermined visual change is indicative of the type of the detected event. The at least one additional image frame is added to the stream of encoded image frames to obtain a combined stream of image frames.

Abstract: Techniques for Long Term Reference (LTR) frame updating in a video encoding process are performed by an image processing device as part of the video encoding process. The method comprises encoding a first LTR frame. The method comprises encoding a plurality of frames referencing directly or indirectly to the first LTR frame. The method comprises sequentially updating the first LTR frame by evaluating a cost for encoding a block of image data in one of the plurality of frames and by updating an image area in the first LTR frame when the cost fulfils a cost criterion. The image area is updated based on the block of image data in at least one of the plurality of frames. The method comprises encoding the sequentially updated first LTR frame as a second LTR frame.

Abstract: A method for encoding lidar data where subsequent frames of lidar data to be encoded are received. Each frame of lidar data comprises a number of lidar return signals for each of a plurality of rays emitted at a respective elevation and azimuth angle by a lidar, and each lidar return signal includes lidar measurement values. Each frame of lidar data is then represented as an image frame of a video sequence, wherein, for each ray of the plurality of rays of the frame of lidar data, lidar measurement values of different lidar return signals are represented in different image portions of the image frame. The different image portions are stacked after each other in a row direction or a column direction of the image frame. The video sequence is then encoded using video encoding.

Abstract: A method of detecting a change of ratio of occlusion of a tracked object in a video sequence. For each of a plurality of image frames, a bounding box of the tracked object is determined and for each pair of successive image frames, an intersection over union (IoU) of a first bounding box in a first image frame and a second bounding box in a second image frame is calculated. Similarly, for a further pair of successive image frames, a further IoU of a first bounding box in a first image frame of the further pair of successive image frames and a second bounding box in a second image frame of the further pair of successive image frames is calculated. If the further IoU differs from the calculated IoUs by more than a threshold amount, the ratio of occlusion of the tracked object has changed.

Abstract: The present disclosure relates to a method of background modelling for a video stream acquired by a camera having movement capabilities. The method comprises: acquiring a video stream; repeatedly updating a background model for the video stream by analyzing changes in the sequence of image frames and categorizing image areas in the image frames which do not change over time as background; detecting camera movement; performing a reset of the background model by: applying an image segmentation and/or object detection algorithm to identify at least foreground objects; after having performed the reset of the background model, returning to repeatedly updating the background model for the video stream by analyzing changes in the sequence of image frames and categorizing image areas in the image frames which do not change over time as background. The disclosure further relates to an image processing system.

Abstract: A camera arrangement comprises a camera head, a holder ring and a holder base. The camera head has an imaging unit and an interaction portion with constant cross section. The camera holder ring has an inner surface configured to fit onto the interaction portion of the camera head, and the camera holder base has a receptacle orifice dimensioned to receive the camera holder ring fitted onto the interaction portion of the camera head and grip an outer surface of the holder ring. The receptacle orifice has reduced dimensions due to a tightening function to fixate the camera holder ring and the camera head in relation to the camera holder base, and thereby to fixate an orientation of the camera in relation to the camera holder base. The camera holder ring is movable along a length of the interaction portion until the tightening function of the receptacle orifice has been actuated.

Abstract: A system includes a mounting bracket configured for attachment to the surface, a plastic clamp having a base part and a connection part. The mounting bracket is provided with an opening into which the base part of the plastic clamp is insertable with a snap fit and the connection part of the plastic clamp is configured for snap fit engagement with an object attachable to the mounting bracket. The base part comprises two legs, each comprising a guide surface and an L-shaped corner section, the guide surface being configured to engage the mounting bracket in response to insertion of the base part into the opening and the L-shaped corner section being configured to face an edge portion of the opening when the base part has been received by the opening. The legs deflect in response to guide surfaces engaging the mounting bracket so the base part is insertable into opening.

Abstract: A method of encoding an input video including a sequence of video frames as a hybrid video stream, comprises downsampling the input video from an original spatial resolution to a reduced spatial resolution and an intermediate spatial resolution; providing the input video at the reduced spatial resolution to a base encoder to obtain a base encoded stream; providing a first enhancement stream based on first residuals at the intermediate spatial resolution; and providing a second enhancement stream based on second residuals based at the original spatial resolution, which is at least partially encoded using temporal prediction. The method further comprises detecting at least one non-motion region in a video frame, and causing the set of first residuals but not the set of second residuals to vanish throughout the non-motion region.

Abstract: A cable retention arrangement for an electronic device, such as a surveillance camera, comprises a base member and an attachment member releasably attachable to the base member. The base member is provided with a channel configured to receive a cable and arranged in a surface of the base member configured to face the attachment member in an assembled state of the cable retention arrangement in which the attachment member is attached to the base member. The channel extends between a cable entry and a cable exit and the attachment member is provided with a slit which, in the assembled state of the cable retention arrangement, is configured to extend in a direction traversing the channel such that the cable exit of the channel is defined at the intersection of the channel and the slit. The disclosure further relates to an electronic device comprising such a cable retention arrangement.

Abstract: A method, system and software for searching for an object in a forensic search application comprises: determining a plurality of static areas in the scene; obtaining a first image depicting the scene comprising an object; determining a plurality of candidate color transforms; determining a plurality of candidate color values of the object by applying each of the plurality of candidate color transform to third pixel data from the first image, said third pixel data depicting the object in the first image; searching for an object in a forensic search application using a search request comprising a first color value; determining that the first color value matches one or more candidate color values; and returning a search response based at least in part on the object.

Abstract: A method for prioritizing feature extraction for object re-identification in an object tracking application. Region of interests (ROI) for object feature extraction is determined based on motion areas in the image frame. Each object detected in an image frame and which is at least partly overlapping with a ROI is associated with the ROI. A list of candidate objects for feature extraction is determined by, for each ROI associated with two or more objects: adding each object of the two or more objects that is not overlapping with any of the other objects among the two or more objects with more than a threshold amount. From the list of candidate objects, at least one object is selected, and image data of the image frame depicting the selected object is used for determining a feature vector for the selected object.

Abstract: The present disclosure relates to a method performed by a monitoring camera (100) for handling a first and a second video stream (201a, 201b). The monitoring camera (100) obtains a first video stream (201a) from a first image sensor (103a) and a second video stream (201b) from a second image sensor (103b). A field of view of the first video stream (201a) partly overlaps with the second video stream (201b). The monitoring camera (100) identifies a moving object (205) in the overlap area (203). The monitoring camera (100) divides the moving object (205) into a plurality of sub objects (210). The monitoring camera (100) performs a hard handover of the sub objects (210) from the first to the second video stream (201a, 201b) when the sub object (210) is within the overlap area (203) and when a point of the sub object (210) passes a border (208).