公开(公告)号：US20210103781A1

公开(公告)日：2021-04-08

申请号：US17030700

申请日：2020-09-24

Applicant: Axis AB

Inventor： Andres VIGREN ,  Aras PAPADELIS ,  Daniel STÅHL ,  Arnab BHATTACHARJEE

IPC: G06K9/62 ,  G06N3/04

Abstract: Apparatus are provided for generating an object classification for an object, the apparatus comprising an image sensor, a radar sensor, and a processing unit, the processing unit configured to perform the steps of: receiving image data for the object from the image sensor, operating an image-based object classifier on the image data to generate an image-based object classification, receiving radar data for the object from the radar sensor, operating a radar-based object classifier on the radar data to generate a radar-based object classification, selecting between the image-based object classification and the radar-based object classification to output as the object classification for the object, determining if a training condition is met by the radar-based object classification, and training the radar-based object classifier using the image-based object classification when the training condition is met by the radar-based object classification.

公开(公告)号：US20220373669A1

公开(公告)日：2022-11-24

申请号：US17748222

申请日：2022-05-19

Applicant: Axis AB

Inventor： Anders MANNESSON ,  Anton SEDIN ,  Aras PAPADELIS ,  David WADMARK ,  Sebastian HEUNISCH ,  Stefan ADALBJÖRNSSON ,  Daniel STÅHL

IPC: G01S13/536 ,  G01S13/89 ,  G01S7/35 ,  G01S7/41

Abstract: A method for mapping a static scene using a stationary radar unit operative to transmit radar signals towards a scene, the stationary radar unit comprises a set of receiver antennas configured to detect radar signals from arbitrary directions, and the stationary radar unit is configured to measure target velocity in discrete velocity bins, the method comprising: continuously collecting radar signals over time to detect a static scene using the set of receiver antennas; constructing an occupancy map of the static scene using confirmed detections determined from the collected radar signals, where confirmed detections are detections with radar signal strength exceeding a detection threshold and with velocity falling in a zero velocity bin and detections with radar signal strength exceeding the detection threshold and with a non-zero velocity sufficiently low to cause spill over information in the same bin as detections falling in the zero velocity bin.

公开(公告)号：US20250014190A1

公开(公告)日：2025-01-09

申请号：US18762342

申请日：2024-07-02

Applicant: Axis AB

Inventor： Aras PAPADELIS ,  Niclas DANIELSSON

IPC: G06T7/20 ,  G06T7/11 ,  G06T7/70 ,  G06V10/25 ,  G06V10/26 ,  G06V10/762

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.

公开(公告)号：US20220373672A1

公开(公告)日：2022-11-24

申请号：US17748223

申请日：2022-05-19

Applicant: Axis AB

Inventor： Anders MANNESSON ,  André NÜSSLEIN ,  Anton SEDIN ,  Aras PAPADELIS ,  Daniel STÅHL ,  David WADMARK ,  Sebastian HEUNISCH ,  Stefan ADALBJÖRNSSON

IPC: G01S13/88 ,  G06K9/00 ,  G01S13/72

Abstract: A method for classifying tracks in radar detections of a scene acquired by a stationary radar unit, comprises: acquiring radar detections of the scene using the static radar unit; feeding at least a portion of the radar detections into a tracker module for producing track-specific feature data indicating a specific track in the scene, feeding at least a portion of the radar detections into a scene model comprising information about scene-specific features aggregated over time, and information indicating areas in the scene with expected ghost target detections and areas with expected real target detections, wherein at least a subset of the scene-specific features is determined from the radar detections; classifying the specific track as belonging to a real target or to a ghost target by relating the specific track to a position in the scene model.