Embedded neuromorphic vision systems

Abstract

The large body of research in perceptual computing has and will continue to enable many intriguing applications such as augmented reality, driver assistance, and personal analytics. Moreover, as wearable first person computing devices become increasingly popular, the demand for highly interactive perceptual computing applications will increase rapidly. Applications including first person assistance and analytics will be pervasive across retail, automotive, and medical domains. However, the computational requirements demanded by future perceptual computing applications will far exceed the capabilities of traditional vision algorithms that are executed on sequential CPUs and GPUs. Hardware accelerators are recognized as key to surpassing the limits of existing sequential architectures. In particular, brain inspired, or neuromorphic, vision accelerators have the potential to support computationally intensive perception algorithms on resource and power constrained devices.