Abstract: Two complementary methods for the detection of moving objects by a moving observer are described. The first is based on the fact that, in a rigid environment, the projected velocity at any point in the image is constrained to lie on a 1-D locus in velocity space whose parameters depend only on the observer motion. If the observer motion is known, an independently moving object can, in principle, be detected because its projected velocity is unlikely to fall on this locus. We show how this principle can be adapted to use partial information about the motion field and observer motion that can be rapidly computed from real image sequences. The second method utilizes the fact that the apparent motion of a fixed point due to smooth observer motion changes slowly, while the apparent motion of many moving objects such as animals or maneuvering vehicles may change rapidly. The motion field at a given time can thus be used to place constraints on the future motion field which, if violated, indicate the presence of an autonomously maneuvering object. In both cases, the qualitative nature of the constraints allows the methods to be used with the inexact motion information typically available from real image sequences. Implementations of the methods that run in real time on a parallel pipelined image processing system are described.