Datasets:
File size: 2,660 Bytes
3535bad | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | # Real4D data format
## Paths
The first path component identifies the source subset (`dynerf` for N3DV or
`meetroom`), followed by a scene. Within each scene, modalities are grouped so
that large subsets can be downloaded independently.
For trajectory `cam00_01` and zero-based frame index `i`, use file number
`i + 1`:
```text
images/cam00_01/cam00_01_000001.jpg
depths/cam00_01/cam00_01_000001.jpg.geometric.png
depth_vis/cam00_01/cam00_01_000001.jpg
camera_params/cam00_01.json # entry 0
```
## RGB
RGB frames are 8-bit three-channel JPEG files. N3DV-derived frames have size
1352 x 1014; MeetRoom-derived frames have size 1280 x 720.
## Depth
Depth files are single-channel 16-bit PNG images. A stored value `d` represents
`d / 1000` meters. Value zero is the invalid mask and indicates negligible
accumulated opacity. These values are rendered pseudo-labels derived from the
reconstructed dynamic scene, not measurements from a depth sensor.
```python
from PIL import Image
import numpy as np
depth_mm = np.asarray(Image.open(depth_path), dtype=np.uint16)
valid = depth_mm > 0
depth_m = depth_mm.astype(np.float32) / 1000.0
```
`depth_vis` is only a colorized preview and must not be used as numeric depth.
## Camera manifest
Each `<trajectory>.json` is a list of 300 dictionaries in temporal order. The
main fields are:
| Field | Meaning |
|---|---|
| `timestamp` | Scene time in seconds. |
| `w2c` | 4 x 4 world-to-camera homogeneous transform. |
| `R` | 3 x 3 rotation component used by the renderer. |
| `T` | 3-vector translation component used by the renderer. |
| `fl_x`, `fl_y` | Focal lengths in pixels. |
| `cx`, `cy` | Principal point in pixels. |
| `FoVx`, `FoVy` | Horizontal and vertical field of view in radians. |
| `width`, `height` | Image dimensions in pixels. |
| `image_name` | Source reference-camera identifier; not an output filename. |
The camera matrix is analytically prescribed along the interpolation path. It
is exact with respect to that virtual trajectory; it is not an SfM/SLAM
estimate. Load the JSON record at list index `i` together with file number
`i + 1`.
## Trajectories
`cam{a}_{b}` denotes the ordered interpolation from reference camera `a` to
reference camera `b`. Because the pair is ordered, `cam00_01` and `cam01_00`
are distinct. `cam00_00` is a static-viewpoint temporal sequence. Every
trajectory contains 300 frames spanning the scene's 10-second temporal extent.
## Preview videos
`video/<trajectory>_rgb.mp4` and `video/<trajectory>_depth.mp4` are provided for
quick browsing at 30 fps. They are convenience derivatives; image sequences
and camera JSON are the authoritative data.
|