ACTION RECOGNITION IN A VIDEO SEQUENCE
    3.
    发明申请

    公开(公告)号:US20180137362A1

    公开(公告)日:2018-05-17

    申请号:US15812685

    申请日:2017-11-14

    Applicant: Axis AB

    Abstract: A method and system for action recognition in a video sequence is disclosed. The system comprises a camera configured to capture the video sequence and a server configured to perform action recognition. The camera comprises an object identifier that identifies an object of interest in an object image frame of the video sequence; an action candidate recognizer configured to apply a first action recognition algorithm to the object image frame to detect presence of an action candidate; an video extractor configured to produce action image frames of an action video sequence by extracting video data pertaining to a plurality of image frames from the video sequence; and a network interface configured to transfer the action video sequence to the server. The server comprises an action verifier configured to apply a second action recognition algorithm to the action video sequence to verify or reject that the action candidate is an action.

    CONDITIONAL FLOW WITH HARDWARE ACCELERATION

    公开(公告)号:US20170083332A1

    公开(公告)日:2017-03-23

    申请号:US14859041

    申请日:2015-09-18

    Applicant: Axis AB

    CPC classification number: G06F9/30058 G06T1/20

    Abstract: A method and system are disclosed. The method may include receiving instructions in a hardware accelerator coupled to a computing device. The instructions may describe operations and data dependencies between the operations. The operations and the data dependencies may be predetermined. The method may include performing a splitter operation in the hardware accelerator, performing an operation in each of a plurality of branches, and performing a combiner operation in the hardware accelerator.

    Method, system and non-transitory computer-readable media for prioritizing objects for feature extraction

    公开(公告)号:US12293529B2

    公开(公告)日:2025-05-06

    申请号:US18616830

    申请日:2024-03-26

    Applicant: Axis AB

    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.

    Methods and systems for encoding and decoding of video data in connection to performing a search in the video data

    公开(公告)号:US12149710B2

    公开(公告)日:2024-11-19

    申请号:US17942642

    申请日:2022-09-12

    Applicant: Axis AB

    Abstract: There are provided encoding and decoding methods, and corresponding systems which are beneficial in connection to performing a search among regions of interest, ROIs, in encoded video data. In the encoded video data, there are independently decodable ROIs. These ROIs and the encoded video frames in which they are present are identified in metadata which is searched responsive to a search query. The encoded video data further embeds information which associates the ROIs with sets of coding units, CUs, that spatially overlap with the ROIs. In connection to independently decoding the ROIs found in the search, the embedded information is used to identify the sets of CUs to decode.

    Segmentation method
    8.
    发明授权

    公开(公告)号:US12136224B2

    公开(公告)日:2024-11-05

    申请号:US17864400

    申请日:2022-07-14

    Applicant: Axis AB

    Abstract: A method of generating a segmentation outcome which indicates individual instances of one or more object classes for an image in a sequence of images is disclosed. The method comprises: determining (501) a coherent region of the image; processing (502) the image to determine a tensor representing pixel-specific confidence scores; generating (503) a series of temporary segmentation masks for the coherent region, wherein each temporary segmentation mask is generated by interpreting the tensor with respect to a single object class using a different temporary confidence score threshold; evaluating (504) the series of temporary segmentation masks to determine if an object mask condition is met; depending on the outcome of the evaluation, setting (505) the temporary confidence score threshold as a final confidence score threshold for the pixels of the temporary segmentation mask, or setting (505) a default confidence score threshold as a final confidence score threshold for the coherent region; and generating (506) a final segmentation outcome for the image.

    Best Image Crop Selection
    9.
    发明申请

    公开(公告)号:US20190171910A1

    公开(公告)日:2019-06-06

    申请号:US15831638

    申请日:2017-12-05

    Applicant: Axis AB

    Abstract: Methods and apparatus, including computer program products, for creating a quality annotated training data set of images for training a quality estimating neural network. A set of images depicting a same object is received. The images in the set of images have varying image quality. A probe image whose quality is to be estimated is selected from the set of images. A gallery of images is selected from the set of images. The gallery of images does not include the probe image. The probe image is compared to each image in the gallery and a match score is generated for each image comparison. Based on the match scores, a quality value is determined for the probe image. The probe image and its associated quality value are added to a quality annotated training data set for the neural network.

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