Vision processing for control of agile autonomous robots requires low-latency computation,
within a limited power and space budget. This is challenging for conventional computing …

Camera sensors rely on global or rolling shutter functions to expose an image. This fixed
function approach severely limits the sensors' ability to capture high-dynamic-range (HDR) …

Conventional machine vision systems have separate perception, memory, and processing
architectures, which may exacerbate the increasing need for ultrahigh image processing …

Visual understanding of 3-D environments in real time, at low power, is a huge
computational challenge. Often referred to as simultaneous localization and map** …

Environments in which Global Positioning Systems (GPS), or more generally Global
Navigation Satellite System (GNSS), signals are denied or degraded pose problems for the …

The ability to image high-dynamic-range (HDR) scenes is crucial in many computer vision
applications. The dynamic range of conventional sensors, however, is fundamentally limited …

This paper presents a vision-based control strategy for tracking a ground target using a
novel vision sensor featuring a processor for each pixel element. This enables computer …

Visual input can be used to recover the 3-D structure of a scene by estimating distances
(depth) to the observer. Depth estimation is performed in various applications, such as …

Reinterpretable cameras are defined by their post-processing capabilities that exceed
traditional imaging. We present" SoDaCam" that provides reinterpretable cameras at the …

In this paper, we present a 3D imaging system providing a semi-dense depth map, using a
passive, low-power, compact, static, monocular camera. The demonstrated depth estimation …