Event Camera Collision Area Prediction for High Speed Objects
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Solution Overview
Problem
Current drones and self-driving cars face challenges in effectively dodging high-speed small objects due to difficulties in immediate identification of these objects, which complicates collision avoidance.
Innovation Solution
A device and method utilizing an event camera and processor to predict collision areas by obtaining sparse event stream data, encoding it into temporal spatial feature expressions, and using these features to predict collision area categories without requiring prior object type identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional cameras are used to detect high speed small objects, then the system can identify object types, but the detection speed and response time are insufficient for effective collision avoidance
Solution Approach 1:
The patent segments the detection task into two independent parts: (1) collision area prediction using event camera data, and (2) object type identification using traditional vision systems. This segmentation allows the critical collision avoidance function to operate at high speed while object type identification can proceed separately without timing constraints.
Solution Approach 2:
The event camera serves as an intermediary device that captures motion-related visual information at high temporal resolution. It mediates between the high-speed motion of small objects and the processing requirements of the system, providing sparse event stream data that highlights changes in the visual scene without requiring full frame capture.
2Loss of time
If the system waits for complete object identification before taking action, then accurate object type classification is achieved, but the response time is too slow for high speed collision avoidance
Solution Approach 1:
The system performs preliminary action by predicting the collision area based on event camera data before complete object identification is achieved. The temporal spatial feature expression enables the system to anticipate where a collision will occur based on motion patterns, allowing preventive action to be taken while the object is still being fully characterized.
Solution Approach 2:
The patent implements a dynamic decision-making framework where the system can operate at different levels of confidence and detail. The collision prediction module operates continuously at high speed, while object type identification proceeds asynchronously. This dynamic approach allows the system to respond immediately to potential collisions without waiting for complete classification.
3Measurement precision
If high temporal resolution data is captured to track fast moving objects, then collision prediction accuracy improves, but data processing complexity increases
Solution Approach 1:
The system extracts only the essential features from the event stream data that are relevant to collision prediction. The temporal spatial feature expression extracts motion patterns, trajectory information, and spatial-temporal relationships from the sparse event data, discarding redundant information while maintaining prediction accuracy.
Solution Approach 2:
The patent transforms the event stream data into a different parameter space using temporal spatial feature expressions. This transformation changes the representation from raw event coordinates to meaningful features that capture motion dynamics, making the data more suitable for collision prediction while reducing processing complexity.
Data Source
AI summary
Disclosed are a device and a method for predicting a collision area of a high speed small object. The method includes: obtaining, by a processor, a sparse event stream data through an event camera; obtaining, by the processor, an event stream data corresponding to a cumulative time interval by using the sparse event stream data; predicting, by the processor, a collision area category by using a temporal spatial feature expression associated with the event stream data, wherein the collision area category corresponds to a high speed small object, and outputting, by the processor, the collision area category.