Scene-Aware Video Encoder Spatio-Temporal Graph
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video scene analysis methods face inefficiencies due to redundancy in visual scene graphs for 2D video frames, lacking 3D insight, and failing to capture spatio-temporal information, leading to inaccurate results in video-based reasoning tasks.
Innovation Solution
A scene-aware video encoder system transforms video frames into a 2.5D spatio-temporal scene graph, segregating static and dynamic sub-graphs, and using hierarchical latent embeddings to capture spatio-temporal information, enabling accurate video question-answering tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual scene graphs are constructed for every video frame, then video-based reasoning can be performed, but computational redundancy increases for longer video sequences
Solution Approach 1:
The patent extracts and retains only key frames from the video sequence rather than processing every frame. This selective extraction removes redundant information while preserving essential spatio-temporal relationships, thereby reducing computational load without significantly compromising reasoning accuracy.
Solution Approach 2:
The patent transitions from 2D frame-by-frame scene graphs to 4D spatio-temporal scene graphs that incorporate time as an additional dimension. This dimensional transformation enables the system to model object permanence and motion across frames more efficiently, reducing redundancy by representing temporal relationships in a unified spatial-temporal framework.
2Device complexity
If 2D visual scene graphs are used for video frames, then scene representation is simple, but spatio-temporal information and 3D insights are lost
Solution Approach 1:
The patent extends 2D scene graphs to 4D spatio-temporal scene graphs by adding time and depth dimensions. This enables the representation to capture 3D spatial relationships and temporal evolution simultaneously, preserving spatio-temporal information while maintaining a unified graph structure rather than separate processing pipelines.
Solution Approach 2:
The patent introduces dynamic properties to scene graph nodes to represent object permanence and motion across frames. Instead of static 2D representations, nodes evolve temporally with attributes that track object state changes, enabling the system to capture dynamic spatio-temporal relationships while building upon the familiar scene graph framework.
3Reliability
If 2D scene graphs are used, then occlusion problems occur, but 3D space representation is not utilized
Solution Approach 1:
The patent incorporates 3D spatial coordinates into scene graph nodes to represent object positions in three-dimensional space. This enables the system to reason about occlusions and spatial relationships more accurately by understanding depth and volume, allowing objects to be represented with 3D bounding boxes and spatial transformations that resolve occlusion ambiguities present in 2D projections.
Data Source
AI summary
Embodiments of the present disclosure discloses a scene-aware video encoder system. The scene-aware encoder system transforms a sequence of video frames of a video of a scene into a spatio-temporal scene graph. The spatio-temporal scene graph includes nodes representing one or multiple static and dynamic objects in the scene. Each node of the spatio-temporal scene graph describes an appearance, a location, and/or a motion of each of the objects (static and dynamic objects) at different time instances. The nodes of the spatio-temporal scene graph are embedded into a latent space using a spatio-temporal transformer encoding different combinations of different nodes of the spatio-temporal scene graph corresponding to different spatio-temporal volumes of the scene. Each node of the different nodes encoded in each of the combinations is weighted with an attention score determined as a function of similarities of spatio-temporal locations of the different nodes in the combination.