Fusion Dataset Structure¶

TensorBay also defines a uniform fusion dataset format. This topic explains the related concepts. The TensorBay fusion dataset format looks like:

fusion dataset
├── notes
├── catalog
│   ├── subcatalog
│   ├── subcatalog
│   └── ...
├── fusion segment
│   ├── sensors
│   │   ├── sensor
│   │   ├── sensor
│   │   └── ...
│   ├── frame
│   │   ├── data
│   │   └── ...
│   ├── frame
│   │   ├── data
│   │   └── ...
│   └── ...
├── fusion segment
└── ...

fusion dataset¶

Fusion dataset is the topmost concept in TensorBay format. Each fusion dataset includes a catalog and a certain number of fusion segments.

The corresponding class of fusion dataset is FusionDataset.

notes¶

The notes of the fusion dataset is the same as the notes (ref) of the dataset.

catalog & subcatalog in fusion dataset¶

The catalog of the fusion dataset is the same as the catalog (ref) of the dataset.

fusion segment¶

There may be several parts in a fusion dataset. In TensorBay format, each part of the fusion dataset is stored in one fusion segment. Each fusion segment contains a certain number of frames and multiple sensors, from which the data inside the fusion segment are collected.

The corresponding class of fusion segment is FusionSegment.

sensor¶

Sensor represents the device that collects the data inside the fusion segment. Currently, TensorBay supports four sensor types.(Table. 2)

Table 2 supported sensors¶
Supported Sensors	Corresponding Data Type
`Camera`	image
`FisheyeCamera`	image
`Lidar`	point cloud
`Radar`	point cloud

The corresponding class of sensor is Sensor.

frame¶

Frame is the structural level next to the fusion segment. Each frame contains multiple data collected from different sensors at the same time.

The corresponding class of frame is Frame.

data in fusion dataset¶

Each data inside a frame corresponds to a sensor. And the data of the fusion dataset is the same as the data (ref) of the dataset.