nicetoolbox.detectors.feature_detectors.gaze_multiview.gaze_fusion

MultiviewFusion feature detector. Fuses raw per-camera gaze vectors into a single world-space vector.

Classes

GazeFusion

Computes a single 3D gaze vector from multiple camera views and/or multiple algorithms.
class nicetoolbox.detectors.feature_detectors.gaze_multiview.gaze_fusion.GazeFusion(io, data, sequence_context, algorithm_instance: str)[source]

Computes a single 3D gaze vector from multiple camera views and/or multiple algorithms.

Given the fused 3D gaze vectors, the user can optionally select to apply a Savitzky-Golay filter for temporal smoothing. Finally, the fused 3D gaze vectors are projected back to each camera view to obtain 2D gaze points for visualization (If enabled).

Expected Input:

  • Method detectors outputting ‘3d’ array.

  • Shape: (Subjects, Cameras, Frames, 3)

  • Optional: ‘confidence_scores’ (Subjects, Cameras, Frames) for weighted fusion.

Initialize base detector with references.

Subclasses should call super().__init__() and set inference_config.

compute() → Dict[str, Any] | None[source]

Run the fusion pipeline.

Returns:

A list of dictionaries containing fused results.

visualization(result: Dict[str, Any]) → None[source]

Generates visualization images with fused gaze overlays.