3D VISION Microsoſt’s Kinect sensor operates by
projecting a pattern of dots onto a scene with the returning light providing depth information via triangulation. It’s not very exact and it only operates over relatively short distances of a couple of metres. Dawson of Teledyne Dalsa comments: ‘Kinect is an example of a non-traditional machine vision system and I think we’re going to see more of these.’ Tere are many opportunities for 3D vision
Software tools for 3D image processing are becoming more complete. Here, a whole three dimensional area can be subtracted out of the model in Halcon 11
you have to do pre-processing, use blob analysis, determine the relation between objects, identify them, determine the position, and so on. In 3D it’s a little more complex, but it generally corresponds to 2D machine vision.’ Te latest release of Halcon, version 11, offers the full range of these operators allowing the user to program a 3D application in a well know process chain.
Bin picking Te exhibit most oſten shown at trade fairs to demonstrate the power of 3D vision is robotic bin picking. Tis, however, is still in its infancy as far as real-world implementations go. Eckstein comments: ‘Vision for robotics is an important area for 3D. However, bin picking is still a challenge and there’s not a 100 per cent solution to any kind of object yet.’ He says the 3D alignment is possible in terms of vision, but typically there isn’t full 360° of freedom in the robot movement. He adds that it is becoming feasible now though. Techniques such as stereovision and time-of-
flight, which are not necessarily highly accurate, but are good for recognising the shape and orientation of an object, are oſten used for bin picking, palletisation and robot guidance. Te vision system has to tell the robot not just where the item is, but its angle and surface profile so the gripper can pick it up in the right place. Te challenge here is engineering a robust 3D system, as the material being handled and the lighting can all vary dramatically, much more than in classical machine vision applications. Robot bin picking is a newer area for 3D imaging than triangulation and inspection. Williamson states that robotic random part bin
picking and palletising is a growing area and only recently have the techniques and tools started to
become more reliable. ‘Bin picking is an area that potentially could grow quite a lot in the future,’ he says. ‘Tere are a lot of people trying it, but I don’t know many companies that have actually implemented it successfully.’
Money talks Te cost of 3D vision is another barrier for companies to contend with. According to Eckstein, a high-quality 3D sensor can cost between €4,000-15,000, which is a lot of money for most companies. It is slowly coming down in price though and a device like Microsoſt’s Kinect sensor, while not a machine vision sensor per se and won’t give high accuracy or resolution, makes 3D imaging available at an extremely low price. ‘Tere’s now a time- of-flight camera for the mass market for €500 with a decent resolution, which would typically cost ten times that,’ states Eckstein. ‘We can expect in industry in the next two or three years there will be sensors available below €1,000. Tis will have a big impact on 3D imaging.’ Te Kinect sensor is an example of a consumer
outside of the factory floor. For an application like face recognition, for example, 3D imaging can add information to 2D imaging data already acquired, thereby reducing false positives. ‘Tere are all sorts of applications like that where 3D is going to be, if not the core data used for analytics, the supporting data,’ explains Tucakov. Of course, 3D imaging has it’s place just as 2D
techniques have theirs. ‘3D is just another tool in the toolbox,’ comments Pierantonio Boriero, product line manager at Matrox Imaging, adding that 3D shouldn’t detract from the work that needs to be done within 2D imaging. ‘Many might get the perception that it’s all about 3D now because the 2D problem has been solved. Tat’s far from true. Tere are still applications that don’t have any vision at all. Te traceability market is exploding at the moment and that’s all 2D imaging.’ Tis is all to say that 3D imaging won’t solve
Kinect and the
value it has created probably surpasses everything else that’s been done with 3D
everything, but it is a powerful tool and one where a lot of development is taking place. Williamson feels the 3D market is growing at a higher rate than 2D. ‘It’s definitely a key growth area in machine vision and that’s why everyone is so excited about it.’ ‘I’m arguing that 3D is
necessary in the situations where it’s necessary,’ Dawson sums up. ‘We’re seeing more and more places where it is necessary and things that you wouldn’t normally think of
product that can be adapted to machine vision tasks. Vladimir Tucakov, director of business development at Point Grey, comments that Kinect and the ecosystem around it and the value it has created probably surpasses everything else that’s been done with 3D in all spaces of computer vision and machine vision. ‘Tat’s the kind of opportunity there is for 3D in my opinion,’ he states. ‘Tere are all kinds of non-industrial applications in life science, traffic, surveillance, entertainment, and many other areas.’
12 Imaging and Machine Vision Europe • June/July 2012
like collision avoidance in automobiles, gaming and package sorting. Tese are huge markets for machine vision. Particularly automotive, with both Mercedes and Volvo integrating collision avoidance systems on their newest models, based on various forms of 3D imaging. Automotive is a market with potentially millions of orders, although the technology has to be cheap in the first place.’ Overall, 3D vision is an exciting area for the
vision community and while it needs to develop further and won’t solve everything, it does add valuable capabilities to what can be achieved with machine vision. O
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