As a benefactor of the proliferation of large scale integration, traditionally simple and unintelligent devices such as cameras have been transformed into key components of rich and engaging smart environments. By integrating machine perception algorithms, these cognitive cameras have the ability to perceive and understand their environments. A principal barrier to realizing the potential of cognitive cameras has been the absence of sufficient computing power within the device. This is especially true in wearable devices which are limited by both compute capability and energy. Hardware customization and specialization present effective solutions to the power and performance bottlenecks that have limited ubiquitous adoption. This work details the architecture, design, and evaluation of a cognitive camera system that employs custom hardware to meet both power and performance constraints. Furthermore we illustrate its use as an assistance system for the visually impaired.