Abstract: Encoding and decoding methods are employed for toggleable overlays in a video. An encoding method comprises receiving a plurality of image frames; determining one or more overlay image frames each comprising a plurality of toggleable overlays, each toggleable overlay being associated with an identifier. An image frame is associated with an overlay image frame of the one or more overlay image frames. Metadata is added to a header of the image frame, wherein the metadata comprises, for each toggleable overlay of the plurality of toggleable overlays: position data identifying a position of the toggleable overlay in the overlay image frame, size data identifying a size of the toggleable overlay in the overlay image frame, and identification data corresponding to the identifier of the toggleable overlay.

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: 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: The present disclosure relates to methods, systems and non-transitory computer-readable storage mediums for detecting an object of a first object type in a video sequence. A first algorithm is used to detect areas or objects in the scene as captured in the video stream that have an uncertain object type status. A second algorithm is used to provide a background model of the video sequence. For areas or objects having the uncertain object type status, the background model is used to check if the area or object is considered to be part of the background or the foreground in the video sequence. If the area or object is determined to belong to the foreground, the area or object is classified as the first object type. If the area or object is determined to not belong to the foreground, the area or object is not classified as the first object type.

Abstract: A device and a method for buffering a graphical overlay to be applied to an image is disclosed. A graphical overlay description specifying content, size, and position in the image of a graphical element of the graphical overlay is obtained, and the graphical overlay is divided into a plurality of sequential line fragments. For each line fragment it is determined, using the graphical overlay description, whether the line fragment overlaps a part of the graphical element. On condition that the line fragment overlaps a part of the graphical element, information representing the part of the graphical element is buffered in a buffer memory for the line fragment. On condition that the line fragment does not overlap any part of the graphical element, a run-length coding representing identical pixels is buffered in the buffer memory for the line fragment.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for controlling the display of an overlay in a video. An overlay to be displayed in a video is defined. An overlay area is defined, which includes the overlay. At least one foreground object in the video is defined. A spatial overlap between the foreground object and the overlay area is determined. In response to determining that a size of the spatial overlap exceeds a first threshold, the entire overlay is stopped from being displayed within the overlay area.

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: An image-processing device generates a three-dimensional model of a background scene of the image frame based on three-dimensional information about the background scene. The image-processing device defines a three-dimensional bounding box of the object in the three-dimensional model. The image-processing device defines a centre coordinate in the three-dimensional model and a colour value of surface elements of the three-dimensional bounding box. The image-processing device determines a three-dimensional coordinate of a surface in the three-dimensional model which reflects light from a surface element into the camera, by tracing rays from the centre coordinate and based on a normal of the surface. The image-processing device further identifies a first pixel in the image frame corresponding to the three-dimensional coordinate and detects the reflection of the object.

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 method and control unit for object detection in a video stream captured with an image acquisition device, especially for the purpose of anonymizing objects in the video stream.

Abstract: A system and techniques for detecting a reflection of an object in a sequence of image frames. Objects of a given type are detected in the sequence of image frames, and a detection score is determined for each detected object. Distance ratios between unfiltered object position indicators identified for each detected object are determined. A displacement factor is determined for each detected object between a current location of the detected object and a previous location of the detected object. One of the two detected objects which has a lower detection score is a reflection of the other of the two detected objects is determined in response to finding a match between normalized sizes and normalized movements of the detected objects.

Abstract: A method of masking or marking an object in an image stream is provided, including: generating one or more output image streams by processing an input image stream capturing a scene, including discarding pixel information about the scene provided by pixels of the input image stream, such that the discarded pixel information about the scene is not included in any output image stream; and detecting an object in the scene using the discarded pixel information, wherein generating the one or more output image streams includes masking or marking the detected object in at least one output image stream once deciding that the object is at least partially visible within this at least one output image stream. A corresponding device, computer program and computer program product are also provided.

Abstract: A method of masking in an output image stream includes receiving an input image stream capturing a scene, processing the input image stream to generate the output image stream, including using a detector to detect objects in the scene and a tracker to track objects in the scene based on information provided by the detector, and further including to generate a particular output image of the output image stream by checking whether there exists a particular area in the scene in which an evaluation of a historical performance of the detector and/or tracker fulfills at least one condition, and to, if confirming that such a particular area exists, mask the particular area of the scene in the particular output image. A corresponding device, computer program, and computer program product are also provided.

Abstract: A controller interacts with an image processing chain configured to process a video stream captured by a video camera and including an object detection algorithm which outputs a frame-wise detection score for each image region, and a masking function which applies a privacy mask in dependence of the detection score. When the controller detects a sudden change in luminance of a scene which is being imaged the video camera, it maintains or expands, for a period while the video camera is imaging the scene, the privacy mask which was applied at the detected sudden change. The maintaining or expanding of the privacy mask may be achieved by locally reducing a masking threshold applied by the masking function. The expansion of the privacy mask may be gradual over time and related to an estimated speed of a moving object in the scene.