The compute-power required to perform general-purpose manipulation of color video streams is too unwieldy to be worn in a backpack (although I've constructed body-worn computers and other hardware to facilitate very limited forms of reality mediation). In particular, a system with good video-processing capability, such as Cheops  or one or more SGI Reality Engines, may be used remotely by establishing a full-duplex video communications channel between the RM and the host computer(s).
In particular, a high-quality communications link (which I call the `inbound-channel') is used to send the video from my cameras to the remote computer(s), while a lower quality communications link (the `outbound channel') is used to carry the processed signal from the computer back to my HMD. This apparatus is depicted in a simple diagram (Fig 2).
Figure 2: Simple implementation of a reality mediator for use as a personal visual assistant. The camera sends video to one or more more computer systems over a high-quality microwave communications link, which I refer to as the `inbound channel'. The computer system(s) send back the processed image over a UHF communications link which I refer to as the `outbound channel'. Note the designations ``i'' for inbound (e.g. iTx denotes inbound transmitter), and ``o'' for outbound. `visual filter' refers to the process(es) that mediate(s) the visual reality and possibly insert virtual objects into the reality stream.
Ideally both channels would be of high-quality, but the machine-vision algorithms were found to be much more susceptible to noise than was my own vision (e.g. I could still find my way around in a ``noisy'' reality, and still interact with ``snowy'' virtual objects).
WearCam (e.g. Fig 1) permits me to experience any coordinate transformation that can be expressed as a mapping from a 2D domain to a 2D range, in real time (30frames/sec = 60fields/sec) in full color, because a full-size remote computer (e.g. SGI Reality Engine) is used to perform the coordinate transformations. This apparatus allows me to experiment with various computationally-generated coordinate transformations both indoors and outdoors, in a variety of different practical situations. Examples of some useful coordinate transformations appear in Fig 3.
Figure 3: Living in coordinate-transformed worlds: Color video images are transmitted, coordinate-transformed, and then received back at 30 frames per second -- the full frame-rate of the VR4 display device. (top) This `visual filter' might allow a person with very poor vision to read (due to the central portion of the visual field being hyper-foveated for a very high degree of magnification in this area), yet still have good peripheral vision (due to a wide visual field of view arising from demagnified periphery). (bottom) This `visual filter' might allow a person with a scotoma (a blind or dark spot in the visual field) to see more clearly, once having learned the mapping. The visual filter also provides edge enhancement in addition the coordinate transformation. Note the distortion in the cobblestones on the ground and the outdoor stone sculptures.
Researchers at Johns Hopkins University have been experimenting with the use of cameras and head-mounted displays for helping the visually handicapped. Their approach has been to use the optics of the cameras for magnification, together with the contrast adjustments of the video display to increase apparent scene contrast. The real-time visual mappings (Fig 3) successfully implemented using the apparatus of Fig 1 may be combined with these other approaches (using well-designed optics and contrast-enhancement achieved by adjusting the analog circuits in the video display itself).