Older blog entries for motters (starting at number 17)

I've made a modified version of the stereo vision system to detect faces. The face detector looks for 'head and shoulders' type shapes within the stereo image, and doesn't rely on colour as most similar systems do.

The face detector seems to work well provided that the person is within 2 metres of the robot (the effective range of the stereo matching), and I think I could make further additions to estimate the gaze direction of the person and also guess their identity.

I've now finished the first version of my stereoscopic vision demo for Windows. Formerly this only worked under linux, but I've been able to make my way through the jungle of DirectShow to produce a Windows version of the same thing.

The windows version performs significantly faster, since there are no problems with support for the camera image compression.

Since the stereo vision system doesn't rely upon motion detection or having the cameras in a fixed position it would be particularly suitable for mobile robotics. You could use it for visual obstacle avoidance, but my first thought is to use it to produce a more reliable face location system. I've tested the system on my 1.7GHz PC and I think that sort of processing speed is probably the minimum for practical applications.

More tomfoolery continues in the Rodney camp. I've now got both quickcams working under Redhat linux 8.0 and devised a stereo vision demo using a matching algorithm devised by Stan Birchfield.

The matching is far from perfect and frequently subject to phantom detections, but it does seem to be the most successful algorithm that I've come across so far.

Running the quickcams under linux is far from ideal and gives an agonisingly slow frame rate because the images are transfered from the cameras in an uncompressed format.

You can find the source code at http://www.fuzzgun.btinternet.co.uk/rodney/vision.htm

Have been experimenting with various webcams which I might use for the next version of Rodney. All the cameras which I've tried have Direct Media compatible drivers, so that I can access a pair of cameras simultaneously.

The tiny Digital Dream L'espion is about the size of a matchbox and produces an image which is similar in quality to the Quickcam Express. It's very lightweight and would be ideal for a robot of some sort, but I think the way that the USB cable plugs into the side might make it awkward to incorperate into a stereo vision head.

I also have an old pair of USB ZoomCams. I originally intended to use these on the first version of Rodney, but decided against it because the drivers under windows 98 were a bit dodgy to put it mildly. However, under winXP the drivers seem ok. The main advantage of this camera is the quality of the image, which looks significantly cleaner and less grainy than the Quickcams. If I take off the outer shell of the camera to expose the bare circuit it looks like it would be relatively easy to mount this so that it could have both vertical and horizontal movement. I could maybe use half of a ping-pong ball to cover the electronics and make it look aesthetically more like an eye.

I've now got hold of an ASC-16 servo control board from www.medonis.com, which is going to replace the miniSSCs in the next version of Rodney.

The new board will be better because it includes speed/acceleration control in hardware, whereas previously all that was done in software. It also includes a few analogue inputs which might be useful, and it runs off a single 5V power supply, wereas the SSC needed two separate supplies.

I've tried the recently released open edition of Borland's Kylix 3. It looks nice, and completely identical to the windows equivalent C++ Builder which I've been using to develop Rodney's vision system.

Actually, I chose C++ Builder precisely becase I knew that Borland were developing a Linux version. This should mean that I can port Rodney's code to linux with minimal effort, whilst not losing the modern drag and drop type development.

There are a couple of unknowns when dealing with Linux. Firstly is the question of how does video for linux work, and does it support simultaneous access of two cameras. Secondly is the question of how serial comms works under linux. Under windows I'm using the MScomm control, and presumably there is something equivalent in linux.

At last after months of searching the web and asking on newsgroups I've finally managed to get Rodney's two quickcams running at the same time and on the same computer. This may not seem like much, but for me I think this is a significant breakthrough, which should permit some interesting new experiments.

Check out the demo on http://www.fuzzgun.btinternet.co.uk/rodney/vision.htm

In the pipeline are plans for the next version of the Rodney robot, and this may eventually use firewire webcams so that I can get a higher frame rate at large resolutions and without the noise which results from video compression algorithms. Firewire cameras should work with the same WDM system which I've developed already.

- Bob

I've made use of a snake algorithm in order to improve the object detection ability of my Rodney robot. This helps to avoid inappropriate background detections which were previously a problem.

Have a look at some of the results at http://www.fuzzgun.btinternet.co.uk/rodney/vision.htm

After writing the optical flow and segmentation routines for the vision system of my Rodney robot I've now combined the two algorithms to form an object detection system.

The fundamental assumption is that parts of the image which are moving in approximately the same manner usually belong to the same object. Of course this isn't always true, but as a general commonsense rule it holds most of the time.

At the moment the combined method merely highlights areas of the image which it thinks belong to the same object. It doesn't actually carry out any recognition of the identified areas, but that is the logical next step.

Work on Rodney's vision system continues apace. The latest algorithm to be completed is a texture-based segmentation routine. This breaks the image down into a number of coloured blobs.

After some tweaking of the algorithm I've managed to get it working quite well, even on the often poor quality images captured from the robot's webcams. This segmentation routine may be very useful for detecting face-like areas of the image for face recognition. The characteristic shapes produced by different hand movements may also be a strong candidate for recognition using this algorithm.

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