Comparametric HDR (High Dynamic Range) imaging for digital eye glass, wearable cameras, and sousveillance

Wearable computing can be used to both extend the range of human perception, and to share sensory experiences with others. For this objective to be made practical, engineering considerations such as form factor, computational power, and power consumption are critical concerns. In this work, we consider the design of a low-power visual seeing aid, and how to implement computationally-intensive computational photography algorithms in a small form factor with low power consumption. We present realtime an FPGA-based HDR (High Dynamic Range) video processing and filtering by integrating tonal and spatial information obtained from multiple different exposures of the same subject matter. In this embodiment the system captures, in rapid succession, sets of three exposures, “dark”, “medium”, and “light”, over and over again, e.g. “dark”, “medium”, “light”, “dark”, “medium”, “light”, and so on, at 60 frames per second. These exposures are used to determine an estimate of the photoquantity every 1/60th of a second (each time a frame comes in, an estimate goes out). This allows us to build a seeing aid that helps people see better in high contrast scenes, for example, while welding, or in outdoor scenes, or scenes where a bright light is shining directly into the eyes of the wearer. Our system is suitable for being built into eyeglasses or small camera-based, lifeglogging, or gesture-sensing pendants, and other miniature wearable devices, with low-power and compact circuits that can be easily mounted on the body.