Zero-Component Motion Detection (2016)

A Music Visualizer From The Future - emotiscope.rocks

I designed Emotiscope as a powerful bridge between sight and sound, with a focus on imperceptable latency and minimalist design.

EMOTISCOPE PCB

Part Highlights

ESP32-S3 Microcontroller

  • Dual-core 240 MHz (CPU and “GPU”)
  • Emotiscope Engine FW built on new ESP-IDF 5.x
  • Uses Espressif’s ESP-DSP library to perform SIMD operations on 32-bit floating point registers
  • GPU / Core 0:
    • “Light Mode” Renderers (Shaders)
    • Simulated Phosphor Decay
    • Temporal Dithering
    • Incandescent LUT
    • RMT output to LEDs
    • 300-500 FPS
  • CPU / Core 1:
    • IO/touch reading
    • Audio acquisition
    • Goertzel (160 instances)
    • FFT
    • Tempo/phase estimation
    • Autocorrelation
    • WiFi
    • Websocket
    • HTTP
    • Self Profiling
    • 100 FPS

XL-1010RGBC (x128)

  • World’s smallest 8-bit RGB Adressable LEDs (1mm x 1mm)
  • Error diffusion algorithm for temporal dithering
  • Approx. 11-bit range visible to eye after dither trick

SPH-0645 MEMS Microphone

  • I2S Bottom-firing Digital Microphone
  • Sample Rate: 12,800Hz (Custom)
  • Mounted to custom daughter board

The “God Damn Fast Transform”

Actually, “GDFT” is what I call a Goertzel-based Discrete Fourier Transform.

Instead of an FFT where there’s N / 2 frequency bins spaced linearly on the scale, I’ve opted to calculate 64 bins of my own choosing, one at a time. This way, they can be allocated logarithmically to represent every note of the western musical scale between A2 (110Hz) and C8 (4186Hz). That’s the upper 64 keys of a grand piano!