event camera processing

**Event Camera Processing** is the **domain of algorithms designed for Neuromorphic (Event-based) sensors** — which, unlike standard cameras that capture frames at fixed intervals, asynchronously record individual pixel brightness changes ("events") with microsecond latency. **What Is Event Camera Processing?** - **Sensor**: DVS (Dynamic Vision Sensor). - **Data Format**: Stream of asynchronous events $(x, y, t, polarity)$. - **Advantage**: No motion blur, extremely high dynamic range (HDR), ultra-low power, microsecond time resolution. - **Challenge**: Standard CNNs expect dense frames (matrices), not sparse asynchronous event lists. **Why It Matters** - **Drone Racing**: Low latency allows tracking at high speeds where standard cameras blur. - **Robotics**: Robustness to lighting changes (works in pitch dark if there is active sensing, or blinding sun). - **Efficiency**: The sensor sends nothing if nothing moves. **Approaches** - **Event Frames**: Accumulating events into a "picture" to use standard CNNs. - **Voxel Grid**: Converting $(x, y, t)$ into a 3D spatiotemporal volume. - **Spiking Neural Networks (SNNs)**: Native processing of spikes. **Event Camera Processing** is **vision at the speed of light** — discarding the legacy concept of "frames" for a bio-inspired, continuous stream of visual information.