A Technical Art Blog
The stream of our SIGGRAPH Realtime Live demo is up on teh internets. If you haven’t seen the actual live demo, check it out!
I feels amazing to win the award for best Realtime Graphics amongst such industry giants. There are so many companies from so many industries participating now, and the event has grown such much. Feels really humbling to be honored with this for a third year; no pressure!
Last month Dell had the Black Friday in July sale and this beauty was on sale for 500 dollars off, plus 10% if you ordered by phone. I decided it was time to replace my beloved Lenovo x220t.
The Alienware 13 might be ugly and lack a Wacom digitizer, but it does have an nVidia GTX 965M and an OLED screen with 211% sRGB coverage! As the Lenovo Yoga X1 only has integrated graphics, I think the Alienware is the machine for 3D artists.
If you’re a gamer who landed here because you wondered how to get the most out of your amazing display, or wondered why everything is super-red-pink, it’s time to put your big boy pants on! Calibrating the monitor wasn’t so straight forward, but let’s jump into it.
We are going to use an open source Color Management toolkit called ArgyllCMS [Download it here]. It can use many different hardware calibration devices, I have used it with the xRite Huey and the Spyder5.
One thing that’s important to know is that all the sensors are the same, you only pay for software features. If you don’t own a calibrator, you can buy the cheapest Spyder, because it’s the same sensor and you are using this software, not the OEM software.
Next we’re going to use a GUI front end built to make ArgyllCMS more user friendly. It’s called DisplayCAL, but it requires a lot of libs (numPy, wxWidgets, etc) so I recommend downloading this zero install that has everything.
Be sure to set the ‘White level drift compensation’ on. You will need to ignore the RGB adjustment it first asks you to fuss with because there is no RGB adjustment on your monitor.
When you are through, you will see the following (or something like it!):
Note: DisplayCAL can also output a 3d LUT for madVR, which works with any number of video playback apps. Check here to force your browser to use your color management profile. If it’s useful, I can make another post detailing all the different settings and color-managed apps to make use of your monitor.
I hope you found this useful, it should apply to the Lenovo Yoga X1 and any other OLED laptops in the coming months.
The Nikon 400mm 2.8 has a lens hood that costs $400. For this price, you would think they use pretty solid parts, but there is a block that a thumbscrew goes into that’s actually hard plastic. If your lens is in a backpack with the hood attached, this retaining screw will strip.
I have read many forum posts where people begrudgingly REPLACED THE ENTIRE HOOD because of this. People said they contacted Nikon directly and were told there are no replacement parts.
After contacting Nikon, I would like anyone googling for a solution to know that you can order the parts from Nikon, the parts and numbers are pictured above. Contact the Nikon Parts Service at: 310-414-5121
GoPro makes small $250 no-frills video cameras that record 1080p and come in waterproof polycarbonate housings rated to 60m depth. They have a 170º angle of view, glass lens, fixed focus (2.5ft – ∞), f/2.8 aperture, and 2.5 hour battery life. These cameras are ‘bare bones’; there is no way to even know if it’s recording but to look directly into the lens, no backfacing LCD or even blinking LED!
Not Usable Under Water! – I did some test dives as soon as I received the housing and was in for a rude awakening. The glass domed ports blur the image underwater. This is because domed ports create a secondary focal point or ‘virtual image’ underwater that must be focused on. It seems that GoPro did not take this into account; after contacting them directly I was told: “It is not possible at this time for the GoPro Hero to focus in an underwater environment.” One funny thing to point out, the cool underwater videos on GoPro’s own site are not shot with their own lens/housing!
SOLUTION: 3rd Party Lenses or Housing – That’s right, to use your GoPro Hero underwater you have to buy a replacement housing from a 3rd party with flat ports (crisp images underwater). At the time of my writing this, there were none available for the 3d Hero System, so I purchased replacement lenses from Pursuit Diving. These lenses are very soft polycarbonate, and you might want to carry some Novus 2 polish with you as they scratch easily [image]. Mine also had some small areas of blurriness: this is not an ideal solution. Eye of Mine has a complete 3d housing replacement in the works, and GoPro themselves say they are ‘working’ on a solution. Either way, be warned: These cameras are unable to produce decent images underwater!
Poor Dynamic Range / Image Quality – As you see below, bright highlights easily get blown out. They claim the 1/2.5″ CMOS sensor is great for low light (>1.4 V/lux-sec), this may be, but it is woefully bad at images that vary in bright and dark.
Highlights are easily blown out, and create bad image artifacts
The H264 (12mbit) really butchers the image at times (PNG)
Rolling Shutter Artifacts (Wobble or Jelly) – Like most CMOS video cameras, the GoPro has some rolling shutter issues; I would say more than other CMOS cameras I have used. Unfortunately, for a camera that is meant to be strapped to moving objects –this is pretty bad! You have no control over the shutter speed, so unfortunately the less light, the more rolling shutter artifacts. Here’s an example looking out my window, but you can also see this in the Thistlegorm wreck footage below.
There is a great free solution for VirtualDub called DeShaker. For the HD Hero you should enter a rolling shutter amount of 82%.
Poor Battery Retention – On more than one occasion I left full batteries in the camera and did not turn it on for one to two days. I was often surprised to find the batteries low or half-drained. I have many other smaller canon, fuji, etc cameras and they have much better retention.
Before, if you wanted to make a GoPro s3d rig, you had to put both cameras on a plate, then clank it to later sync the videos by audio waveform. Not only that, but the cameras dropped frames, so you had to time warp the footage to take into account drift: It was less than ideal.
In March (2011) GoPro released the ‘3d Hero System’ which is a new housing and a sync cable for two existing cameras. They also purchased CineForm Studio and skinned the software to make for a slightly less painful s3d workflow; unless you know what you’re doing, then their CineForm app can be pretty obnoxious/unintuitive.
Somewhat Buggy / Unreliable
I was surprised by the bugs I encountered. It’s very frustrating to think you are recording something and later realize that the camera rig left you with unusable data. For instance, I thought the cameras were recording for an entire dive, but it turned out that they somehow entered a state where they made 400+ individual one second MP4 files. Other times one camera would turn off, or unsync and begin recording in a separate format (like one eye 1080p, the other 5mp stills). Many times one battery would run out well before the other, in which case you at least have 2d video, but still annoying.
Sync Cable does not ‘Sync’ Cameras
The ‘Sync Cable’ does not really ‘sync’ the cameras; treating it as a sync cable will only lead to complete frustration. This can really cause some issues, you need to think of the cable as a ‘controller cable’, where one camera is the master and the other a slave, or you will end up with only one camera recording. Again, the functions of the cameras are not sync’d! The Camera with the sync cable marked ‘R’ must start/stop the recording for both cameras to record. It is easy to place the cameras in the housing so that the ‘slave’ camera shutter button is pressed, this does not work, so be careful!
Here is a schematic of the ‘sync cable’ for DIY people.
Sync’d Recording Not Perfect (Don’t think ‘Genlock’)
While better than clanging a metal bar and timewarping to the audio, the sync cable doesn’t really sync the sensors. The videos seem a full frame off, so maybe the CineForm software compensates for this.
As you can see, the right (master) camera is a frame or so ahead of the left
Camera Settings Like White Balance and Exposure NOT Sync’d
Many times I find myself with stereo video where each eye is widely different. Whether it’s exposure, white balance, etc.. it’s frustrating, and the included CineForm software doesn’t offer much of a solution.
CineForm Software is Slow, Can be Frustrating
An example of some frustration advanced users may have is: “EXPORT TO MP4”: just a big button, nothing about datarate or other export options.. just a button. Unfortunately the UI has been dumbed down to the point of ambiguity and frustration. They should have continued and just made a “UPLOAD TO YOUTUBE 3D” because the software is dumbed down to the point of not being useful to advanced users, but not being easy enough for novices.
Fixed Interocular
The interocular of the housing is ~3.5cm which is a bit too close for my liking. Reducing the interocular to something smaller than the distance between your eyes causes the 3d effect to be weakened and things to appear larger than they really are. The interocular was decent for underwater, and I guess if you are filming yourself on a surfboard, but not great for driving through the Serengeti. The sync cable is of fixed length, so you cannot use it with other GoPro housings.
Unable to Use Other Attachments
Because the sync cable uses the expansion port, and the housing doesn’t accomodate, you cannot use the LCD backpac or the larger battery with the 3D Hero System.
Sure I pointed out a lot of issues that I had, but for the price, the GoPro system is pretty great. The housing, though cheap, never flooded (many 30m dives). This is the first footage I have posted, and I have not post-processed it much. I will maybe make another post once I figure out the best ways to automatically post-process the footage to remove artifacts and distortion.
click to enlarge
I have been researching the best options available for the D300 when it comes to quickly generating some lightprobes/panoramas. This of course means fisheye lenses. Currently, Sigma is the only company that makes a 180 degree circular fisheye. They come in two flavors, 8mm, and 4.5mm. The 8mm projects a full circle onto a full 35mm sensor (full frame), but on an APS-C sensor it is cropped. The 4.5mm however, throws a perfect circular image onto an APS-C sized sensor; I believe it is the only lens that does this.
You would think that the 4.5mm would be the way to go, I did until I took a look at both. It really comes down to the pixels. The width in pixels of the image thrown by the 4.5mm lens is roughly 2285px in diameter. So while you can shoot less, an entire panorama taking about 3 shots, it will come out as a <4k equirectangular. However, using the 8mm, you need 4 shots, plus one zenith (5 shots total) and it generates an 8k image. While the 4.5mm does generate a 180 degree image across, as you can see it is very wasteful.
So why doesn’t the lens have full coverage in at least the short dimension? I think it’s because it’s a lens designed to fit Canon and Sigma cameras, not just Nikon. Canon sensors have a 1.6 crop factor and Sigma’s Foveon X3 has a 1.7 crop factor (13.8mm)! The coverage is so small because Nikon DX format has a 1.5 crop factor, the APS-C sensor is much larger than Canon or Sigma. The actual circle measures 12.3mm, even small for the Sigma, which makes me believe they future-proofed it for Four Thirds.
For an APS-C sensor like the D300, I would recommend the 8mm, unless you really need a full uncropped image. The 4.5mm, while being more expensive, also has an aperture of 2.8, compared to the 8mm (f/3.5)
I am not super constrained on time, if you are on set and shooting bracketed probes between takes or something, the 4.5mm will save you two shots (18 pictures) and this might be preferable. That said, it will only generate a 4k image in the end (which might be enough)
Many, many people are having weird, buggy camera issues where you rotate a view and it snaps back to the pre-tumbled state (view does not update properly). There are posts all over, and Autodesk’s official response is “Consumer gaming videocards are not supported”. Really? That’s basically saying: All consumer video cards, gaming or not, are unsupported. I have had this issue on my laptop, which is surely not a ‘gaming’ machine. Autodesk says the ‘fix’ is to upgrade to an expensive pro-level video card. But what they maybe would tell you if they weren’t partnered with nVidia is: It’s an easy fix!
Find your Maya ENV file:
C:\Documents and Settings\Administrator\My Documents\maya\2009-x64\Maya.env
And add this environment variable to it:
MAYA_GEFORCE_SKIP_OVERLAY=1
Autodesk buried this information in their Maya 2009 Late Breaking Release Notes, and it fixes the issue completely! However, even on their official forum, Autodesk employees and moderators reply to these draw errors as follows:
Maya 2009 was tested with a finite number of graphics cards from ATI and Nvidia, with drivers from each vendor that provided the best performance, with the least amount of issues. (at the time of product launch). A list of officially qualified hardware can be found here: http://www.autodesk.com/maya-hardware. Maya is not qualified/supported on consumer gaming cards. Geforce card users can expect to have issues. This is clearly stated in the official qualification charts mentioned above.
The market is flooded with cheap ‘TN’ TFT panels. TN (twisted nematic) panels are terrible when it comes to reproducing color and have a very limited viewing angle. I used to have one and if I just slouched in my chair (or sat up too straight) the black level would change drastically. These panels are much cheaper to manufacture, so vendors have been flocking to them for years.
As artists, we need at least _decent_ color, even on our home machines. Because it can sometimes be difficult to determine the actual panel used in a diaplay, and because I care, I have compiled a list of > 24″ monitors and their panel type. I really would have liked to have seen this last week.
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I really needed a stick of 800mhz DDR2. There’s a Best Buy somewhat close to here so I went over. When I get there, I see they have one stick of Kingston Value RAM, however it’s 145 DOLLARS. Thinking this was clearly a typo, I headed to the ‘Geek Squad’ guy at the register who scanned it and told me:
‘Nope, that’s how much this kind of RAM costs, it’s really a special kind‘. (yeah ‘value’)
I replied that it certainly was not. That is should be under 50 bucks ‘at any store’, he then laughed and told me that they match prices, but not ‘online only stores‘, to which I replied: ‘name a store, any store and that’s the price I will use‘. He said Fry’s (a popular brick and mortar store in Palo Alto) and we pulled up the website. The same RAM was 33 DOLLARS! Not on sale; nothing.
He called the manager, who came and said they couldn’t price match with a difference that large. I leveled with them… ‘Guys, look, it’s one stick of ‘value’ RAM. My PC is broken. I rode my bike here. Fry’s is in Palo Alto. I would pay double what it is at Frys, I am not tryin to rip you off, but I will not, on principle, bend over and take it like this; five times normal retail price is ridiculous!‘
The manager, seeing people behind me, started to talk down to me ‘We aren’t ripping you off, you are trying to price match to another store’s black friday ad! we only price match to real, non-sale prices!‘
I said ‘Look, it’s not a sale item, your own guy brought it up, name any store, where will you price match to?‘ He thought for a min ‘Central Computers, on Howard..‘ (they are not a chain and it would probably be more expensive..) ‘Ok, pull that up!’ We pulled the site up and the ram was 34 DOLLARS!
He turned to me quietly: ‘50 is as low as we can go.‘Â Â ‘Sold!‘
I used to think Best Buy was decent, when you needed a component, if they had it, why go anywhere else? They are such a large chain that they can really discount items because they purchase in bulk. Like I said, this is what I used to think… While I have been in Germany the past 4 years apparently things have changed.
Have any of you seen anything this bad? Charging $145 for something all other retailers have for < $35 is just wrong. It irks me that they pay these ‘geeks’ in their ‘squad’ to tell people lies from behind this knowledgeable facade.
I have seen some of the other material in the SIGGRAPH Image Metrics presskit posted online [Emily Tech Demo] [‘How To’ video], but not the video that shows the making of the Emily tech demo. So here’s that as well:
At the end, there’s a quote from Peter Plantec about how Image Metrics has finally ‘crossed the uncanny valley’, but seriously, am I the only one who thinks the shading is a bit off, and besides that, what’s the point of laying a duplicate of face directly on top of one in a video? Shouldn’t they have shown her talking in a different setting? Maybe showed how they can remap the animation to a different face? There is no reason not to just use the original plate in this example.
Facial motion capture stabilization is basically where you isolate the movement of the face from the movement of the head. This sounds pretty simple, but it is actually a really difficult problem. In this post I will talk about the general process and give you an example facial stabilization python script.
Disclaimer: The script I have written here is loosely adapted from a MEL script in the book Mocap for Artists, and not something proprietary to Crytek. This is a great book for people of all experience levels, and has a chapter dedicated to facial mocap. Lastly, this script is not padded out or optimized.
To follow this you will need some facial mocap data, there is some freely downloadable here at www.mocap.lt. Grab the FBX file.
Get at least 3 markers on the actor that do not move when they move their face. These are called ’stabilization markers’ (STAB markers). You will use these markers to create a coordinate space for the head, so it is important that they not move. STAB markers are commonly found on the left and right temple, and nose bridge. Using a headband and creating virtual markers from multiple solid left/right markers works even better. Headbands move, it’s good to keep this in mind, above you see a special headrig used on Kong to create stable markers.
It is a good idea to write some tools to help you out here. At work I have written tools to parse a performance and tell me the most stable markers at any given time, if you have this data, you can also blend between them.
Load up the facial mocap file you have downloaded, it should look something like this:
In the data we have, you can delete the root, the headband markers, as well as 1-RTMPL, 1-LTMPL, and 1-MNOSE could all be considered STAB markers.
As you can see, mocap data is just a bunch of translating points. So what we want to do is create a new coordinate system that has the motion of the head, and then use this to isolate the facial movement.
This will take some processing, and also an interactive user interface. You may have seen my tutorial on Creating Interactive MotionBuilder User Interface Tools. You should familiarize yourself with that because this will build on it. Below is the basic idea:
You create a library ‘myLib’ that you load into motionbuilder’s python environment. This is what does the heavy lifting, I say this because you don’t want to do things like send the position of every marker, every frame to your external app via telnet. I also load pyEuclid, a great vector library, because I didn’t feel like writing my own vector class. (MBuilder has no vector class)
So we will now create our own library that sits inside MBuilder, this will essentially be a ‘toolkit’ that we communicate with from the outside. Your ‘myLib’ can be called anything, but this should be the place you store functions that do the real processing jobs, you will feed into to them from the outside UI later. The first thing you will need inside the MB python environment is something to cast FBVector3D types into pyEuclid. This is fairly simple:
#casts point3 strings to pyEuclid vectors def vec3(point3): return Vector3(point3[0], point3[1], point3[2]) #casts a pyEuclid vector to FBVector3d def fbv(point3): return FBVector3d(point3.x, point3.y, point3.z) |
Next is something that will return an FBModelList of models from an array of names, this is important later when we want to feed in model lists from our external app:
#returns an array of models when given an array of model names #useful with external apps/telnetlib ui def modelsFromStrings(modelNames): output = [] for name in modelNames: output.append(FBFindModelByName(name)) return output |
Now, if you were to take these snippets and save them as a file called myLib.py in your MBuilder directory tree (MotionBuilder75 Ext2\bin\x64\python\lib), you can load them into the MBuilder environment. (You should have also placed pyEuclid here)
In the image above, I get the position of a model in MBuilder, it returns as a FBVector3D, I then import myLib and pyEuclid and use our function above to ‘cast’ the FBVector3d to a pyEuclid vector. It can now be added, subtracted, multiplied, and more; all things that are not possible with the default MBuilder python tools. Our other function ‘fbv()‘ casts pyEuclid vectors back to FBVector3d, so that MBuilder can read them.
So we can now do vector math in motionbuilder! Next we will add some code to our ‘myLib’ that stabilizes the face.
One thing we will need to do a lot is generate ‘virtual markers’ from the existing markers. To do this, we need a function that returns the average position of however many vectors (marker positions) it is fed.
#returns average position of an FBModelList as FBVector3d def avgPos(models): mLen = len(models) if mLen == 1: return models[0].Translation total = vec3(models[0].Translation) for i in range (1, mLen): total += vec3(models[i].Translation) avgTranslation = total/mLen return fbv(avgTranslation) |
Here is an example of avgPos() in use:
Now onto the stabilization code:
#stabilizes face markers, input 4 FBModelList arrays, leaveOrig for leaving original markers def stab(right,left,center,markers,leaveOrig): pMatrix = FBMatrix() lSystem=FBSystem() lScene = lSystem.Scene newMarkers = [] def faceOrient(): lScene.Evaluate() Rpos = vec3(avgPos(right)) Lpos = vec3(avgPos(left)) Cpos = vec3(avgPos(center)) #build the coordinate system of the head faceAttach.GetMatrix(pMatrix) xVec = (Cpos - Rpos) xVec = xVec.normalize() zVec = ((Cpos - vec3(faceAttach.Translation)).normalize()).cross(xVec) zVec = zVec.normalize() yVec = xVec.cross(zVec) yVec = yVec.normalize() facePos = (Rpos + Lpos)/2 pMatrix[0] = xVec.x pMatrix[1] = xVec.y pMatrix[2] = xVec.z pMatrix[4] = yVec.x pMatrix[5] = yVec.y pMatrix[6] = yVec.z pMatrix[8] = zVec.x pMatrix[9] = zVec.y pMatrix[10] = zVec.z pMatrix[12] = facePos.x pMatrix[13] = facePos.y pMatrix[14] = facePos.z faceAttach.SetMatrix(pMatrix,FBModelTransformationMatrix.kModelTransformation,True) lScene.Evaluate() #keys the translation and rotation of an animNodeList def keyTransRot(animNodeList): for lNode in animNodeList: if (lNode.Name == 'Lcl Translation'): lNode.KeyCandidate() if (lNode.Name == 'Lcl Rotation'): lNode.KeyCandidate() Rpos = vec3(avgPos(right)) Lpos = vec3(avgPos(left)) Cpos = vec3(avgPos(center)) #create a null that will visualize the head coordsys, then position and orient it faceAttach = FBModelNull("faceAttach") faceAttach.Show = True faceAttach.Translation = fbv((Rpos + Lpos)/2) faceOrient() #create new set of stabilized nulls, non-destructive, this should be tied to 'leaveOrig' later for obj in markers: new = FBModelNull(obj.Name + '_stab') newTran = vec3(obj.Translation) new.Translation = fbv(newTran) new.Show = True new.Size = 20 new.Parent = faceAttach newMarkers.append(new) lPlayerControl = FBPlayerControl() lPlayerControl.GotoStart() FStart = int(lPlayerControl.ZoomWindowStart.GetFrame(True)) FStop = int(lPlayerControl.ZoomWindowStop.GetFrame(True)) animNodes = faceAttach.AnimationNode.Nodes for frame in range(FStart,FStop): #build proper head coordsys faceOrient() #update stabilized markers and key them for m in range (0,len(newMarkers)): markerAnimNodes = newMarkers[m].AnimationNode.Nodes newMarkers[m].SetVector(markers[m].Translation.Data) lScene.Evaluate() keyTransRot(markerAnimNodes) keyTransRot(animNodes) lPlayerControl.StepForward() |
We feed our ‘stab‘ function FBModelLists of right, left, and center stabilization markers, it creates virtual markers from these groups. Then ‘markers’ is all the markers to be stabilized. ‘leavrOrig’ is an option I usually add, this allows for non-destructive use, I have just made the fn leave original in this example, as I favor this, so this option does nothing, but you could add it. With the original markers left, you can immediately see if there was an error in your script. (new motion should match orig)
Earlier I mentioned Creating Interactive MotionBuilder User Interface Tools, where I explain how to screenscrape/use the telnet Python Remote Server to create an interactive external UI that floats as a window in MotionBuilder itself. I also use the libraries mentioned in the above article.
The code for the facial stabilization UI I have created is here: [stab_ui.py]
I will now step through code snippets pertaining to our facial STAB tool:
def getSelection(): selectedItems = [] mbPipe("selectedModels = FBModelList()") mbPipe("FBGetSelectedModels(selectedModels,None,True)") for item in (mbPipe("for item in selectedModels: print item.Name")): selectedItems.append(item) return selectedItems |
This returns a list of strings that are the currently selected models in MBuilder. This is the main thing that our external UI does. The person needs to interactively choose the right, left, and center markers, then all the markers that will be stabilized.
At the left here you see what the UI looks like. To add some feedback to the buttons, you can make them change to reflect that the user has selected markers. We do so by changing the button text.
Example:
def rStabClick(self,event): self.rStabMarkers = getSelection() print str(self.rStabMarkers) self.rStab.Label = (str(len(self.rStabMarkers)) + " Right Markers") |
This also stores all the markers the user has chosen into the variable ‘rStabMarkers‘. Once we have all the markers the user has chosen, we need to send them to ‘myLib‘ in MBuilder so that it can run our ‘stab‘ function on them. This will happen when they click ‘Stabilize Markerset‘.
def stabilizeClick(self,event): mbPipe('from euclid import *') mbPipe('from myLib import *') mbPipe('rStab = modelsFromStrings(' + str(self.rStabMarkers) + ')') mbPipe('lStab = modelsFromStrings(' + str(self.lStabMarkers) + ')') mbPipe('cStab = modelsFromStrings(' + str(self.cStabMarkers) + ')') mbPipe('markerset = modelsFromStrings(' + str(self.mSetMarkers) + ')') mbPipe('stab(rStab,lStab,cStab,markerset,False)') |
Above we now use ‘modelsFromStrings‘ to feed ‘myLib’ the names of selected models. When you run this on thousands of frames, it will actually hang for up to a minute or two while it does all the processing. I discuss optimizations below. Here is a video of what you should have when stabilization is complete:
Remember: Your stabilization will only be as good as your STAB markers. It really pays off to create tools to check marker stability.
Sometimes the terminal/screen scraping runs into issues. The mbPipe function can be padded out a lot and made more robust, this here was just an example. If you look at the external python console, you can see exactly what mbPipe is sending to MBuilder, and what it is receiving back through the terminal:
Sending>>> selectedModels = FBModelList() Sending>>> FBGetSelectedModels(selectedModels,None,True) Sending>>> for item in selectedModels: print item.Name ['Subject 1-RH1', 'Subject 1-RTMPL'] |
All of the above can be padded out and optimized. For instance, you could try to do everything without a single lPlayerControl.StepForward() or lScene.Evaluate(), but this takes a lot of MotionBuilder/programming knowhow; it involves only using the keyframe data to generate your matrices, positions etc, and never querying a model.
This is a video from a company called Immersive Media. It’s a 360 degree streaming video you can pan around, and even zoom in. Awesome stuff, their hardware even does realtime stitching, and they have an underwater housing. Check out the site for more vids, they have been to some great locations.
At work we got the Casio EX-F1 for animation reference. It’s a really great, cheap solution for those looking to record high speed reference (300/600/1200fps) or hd (1080) video. Here are some videos I took a few weeks ago:
Vicon Datastations allow you to string off a remote trigger which can allow you to start and stop of a motion capture take with a physical button. This could allow you to start/stop motion capture with sensors or anything else. In our case, we wanted to start/stop another device at the same exact time and have it sync’d with the mocap data, also, allow one person to run the device and the mocap session.
Disclaimer: I am aware that the remote interface is the same for the V8i/612/624/460/V6 Datastations, but I built this for the V8i, which looks like this:
This is what the ‘J1 REMOTE‘ port looks like on the back of your Datastation:
Here is the description of the J1 Remote in the Vicon hardware manual:
Located directly below the camera inter face connectors, the J1 connector function is to allow the remote control of data capture from external switches or photoelectric sensors. Connecting Start (pin 3) or Stop (pin 5) to Ground (pin 7) will initiate the selected function. Pin 1 generates a negative going TTL gated reference signal, which is aligned, to the camera Horizontal Synchronisation (HD) signal and present when data capture is being per formed.
The hardware manual will tell you that the J1 Remote Interface Connector is a Lemo Part (FGG.1B.307.CLAD52). So you will have to order this (follow the link). Below is the pin out from the manual, it’s pretty simple stuff:
So, what we want to do is make a start and a stop button, or you could make an on/off switch. I made a button. The button flips a relay, which is like a switch. Below you see 5 pins, labeled ‘start‘, ‘stop‘, ‘grnd‘ and ‘coil‘. When you apply power to the coil, it will connect the grnd from stop to start and vice versa. Because it’s a magnet that flips the switch, nothing from the inner circuitry of the trigger can send any interference to the Vicon Datastation.
Below you see two relays, one triggers start/stop, the other triggers an LED. You can get relays that flip multiple poles at once. If you wanted to start/stop other devices with the same buttons you would add more relays, or use a multi-pole. In my example below I was sure to get relays and LEDs that work with a 9v battery, this way you do not need resistors or anything to alter the voltage.
This is what a final remote trigger can look like, green starts, red stops. The green LED can be on while capturing. The above relay will flip the light on/off based on button contact, even if red is pressed first, so you may want to go a different route if someone has butter fingers. The cord is durable microphone cord, as we only need 3 wires (start/stop/grnd, mic cable =Â left/right/grnd).
Note: The J1 Remote Trigger works in Vicon Workstation, however, when Vicon updated it’s software to IQ, they did not want to spend the time to continue support of the remote trigger. IQ supports newer technology like the ‘MX Remote’ made by Vicon, which they would rather have you purchase. So yes, if you update your Vicon Software, certain features of your Vicon hardware will become useless.
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