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Multiple Extended Object Tracking

In traditional tracking systems, the point target model is commonly used. In a point target model:

  • Each object is modeled as a point without any spatial extent.

  • Each object gives rise to at most one measurement per sensor scan.

虽然点目标模型简化了跟踪系统，但是当考虑现代跟踪系统时，上面的假设可能无效：

  • In modern tracking systems, the dimensions of the extended object play a significant role. For example, in autonomous vehicles, target dimensions must be considered properly to avoid collision with objects around the autonomous system.

  • Modern sensors have a high resolution, and an object can occupy more than one resolution cell. As a result, the sensor may report multiple detections for that object. In this case, the point model cannot fully exploit the sensor ability to detect object extent.

In extended object tracking, a sensor can return multiple detections per scan for an extended object. The differences between extended object tracking and point object tracking are more about the sensor properties rather than object properties. For example, if the resolution of a sensor is high enough, even an object with small dimensions can still occupy several resolution cells of the sensor.

传感器融合和跟踪工具箱™ offers several methods and examples for multiple extended object tracking. Depending on the assumptions made in the detection and tracker, these methods can be separated into the following categories:

  • One detection per object.

    In this category, the conventional trackers (such astrackerGNN,trackerJPDA, andtrackerTOMHT使用）用于每个对象的一个​​检测。此类别可以进一步分为两种方法：

    • A point detection per object.

      In this method, even though the sensor returns multiple detections per object, these detections are first converted into one representative point detection with certain covariance to account for the distribution of these detections. Then the representative point detection is processed by a conventional tracker, which models the object as a point target and tracks its kinematic state. Even though this method is simple to use, it overlooks the ability of the sensor to detect the object dimension.

      The Point Object Tracker approach shown in the first part ofExtended Object Tracking of Highway Vehicles with Radar and Cameraexample adopts this method.

    • An extended object detection per object.

      在该方法中，将扩展对象的多次检测转换为单个参数化形状检测。形状检测包括物体的运动状态，以及其范围参数，例如长度，宽度和高度。然后，通过传统的跟踪器处理形状检测，该跟踪器通过跟踪对象运动状态及其尺寸来将对象绘制为扩展对象。

      In the使用LIDAR跟踪车辆：从点云到跟踪列表example, the Lidar detections of each vehicle are converted into a cuboid detection with length, width, and height. A JPDA tracker is used to track the position, velocity and dimensions for all the vehicles with these cuboid detections.

  • Multiple detections per object.

    在此类别中，扩展对象跟踪器（例如trackerPHD),假设multiple detections per object. The detections are fed directly to the tracker, and the tracker models the extended object using certain default geometric shapes with variable sizes.

    In theExtended Object Tracking of Highway Vehicles with Radar and Cameraexample, the GGIW-PHD Extended Object Tracker approach represents vehicle shapes as ellipses, and the GM-PHD Tracker approach represents vehicle shapes as rectangles.

    In theExtended Object Tracking With Radar For Marine Surveillanceexample, the GGIW-PHD tracker models the ship shapes as ellipses.