In computer vision for object recognition or navigation, shadows are a frequent occurrence. However, shadows are difficult to recognize because they cannot be infallibly recognized until a scene's geometry and lighting are known. We present a number of cues which together strongly suggest the identification of a shadow and which can be examined without a high computational cost. The techniques developed are: a color model for shadows and a color image segmentation method that recovers single material surfaces as single image regions irregardless of whether the surface is partially in shadow; a method to recover the penumbra and umbra of shadows; and, a method for determining whether some object could be obstructing a light source. These cues either depend on or their reliability improves with the examination of some well understood shadows in a scene. Our observer is equipped with an extendable probe for casting its own shadows. These actively obtained shadows allow the observer to experimentally determine the number, location, and rough extent of the light sources in the scene. The system has been tested against a variety of indoor and outdoor environments.