Axis Ab

Ludvig Hassbring

Song Yuan

Jessica Nilsson

Johan Nyström

Tim Borglund

Mikael Murstam

Michael Barnes

A method for rendering a text string in a digital raster image suitable for block-wise transform coding, the method comprising: obtaining a partition of an image area into coding blocks for the block-wise transform coding; representing the text string as a plurality of graphical elements from a typeface which are arranged according to a tentative layout in the image area, wherein the tentative layout defines at least a position, orientation and size of each graphical element; modifying the tentative layout by applying a spectrum sparsening operation to at least one nonempty coding block, thereby obtaining a modified layout; and rendering a digital raster image of the graphical elements arranged according to the modified layout.

Encoder-optimized text rendering

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.

Methods, systems and non-transitory computer-readable storage mediums for detecting an object of a first object type in a video sequence

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.

Video monitoring with robust privacy masking

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.

Method and device for determining that a detected object belongs to a specific class

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.

Method and image-processing device for determining a probability value indicating that an object captured in a stream of image frames belongs to an object type

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.

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Lund, Sweden

Ludvig Hassbring