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20181019 Seamless Looping Noise - YouTube


I've just finished producing another video that shows how to seamlessly loop animated noise in almost any 3D, compositing, and even video editing software.
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Maya Expressions Part 05 - Random values - YouTube

In Maya Expressions Part 05, we take a look at random numbers, how Maya generates them, and how we can use them in our expressions. Finally, we put it to use in a simple instrument indicator needle animation.
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Matthew Merkovich Says To Stop With The Crazy Tracking Markers

Today I came across a great interview with Matthew Merkovich on LesterBanks dated 2 years ago.

He's a very experienced CG artist. Having spent many years doing matchmove, he gave some of his insights into the quirkiness surrounding the craft and many misunderstood practices that may not be applicable given the capabilities and accuracy of the software tools available to us in the present day.

One of the points he raised is relating to the practice of placing red/orange crosses for markers during location shooting simply because they are told it is the best way to do things.

On top of this, in the interview he also has a list of matchmoving dos and don'ts, advice and tips!

Matthew also has a series of videos showing many matchmove tutorials. Follow him on Vimeo!

Tracking Marker Guidelines - Vimeo
Tracking Marker Guidelines from MattMerk on Vimeo.

As an artist that has been doing matchmoving for no small number of years, I am gladdened to have come to agree with many of Matthew's advice.

One of the things that I hear many a co-worker ask for is on-set data, camera info sheet, etc. For many years large and structured VFX facilities have relied on them because they are meticulously taken and recorded down, especially on very large productions. We only get this on the most organised shoots and even then human errors are commonplace when the person measuring it does not fully understand how it needs to be used downstream

One of Matthew's observations I find interesting is that matchmove software of today are already capable of getting accurate solve without needing much camera-specific information. Sometimes errorneous camera readings and information get in the way of the solve instead of helping it.

This scenario is a commonplace-occurance in today's VFX production. Not all location shoots will come back with reliable per-shot camera data and measurements that big pipelines require for their plates to push through.

Thus as an independent freelancer and as an artist working on a smaller scale production nowadays, almost every matchmove project I encounter does not have adequate camera data, if at all. I find myself not needing to ask for camera data. You may think this is an extreme case but it is not. This is actually commonplace.

However, saying that the matchmove process does not require any camera information is probably slightly misleading. I think it's always safe to have camera data, however accurate. Afterall, matchmoving is replicating camera attributes and movement. I see camera data as a back-up and as an instrument to confirm and affirm, for very tough shots when too many variables are involved, when any known variable from data taken from the set would eliminate guesswork and help to greatly speed up the matchmove process.
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Today I came across a post on Foundary's website about data analysis and matchmoving.

Alastair Barber tries to improve and speed up the pipeline with data analysis and algorithms while working with DNEG.

Matchmoving is something close to my heart. I started my Hollywood film career as a matchmove artist. I'm also quite interested in machine learning, data analysis and artificial intelligence. Thus this article grabbed my attention.

It seems that DNEG is a great choice for data analysis, having accumulated 20 years of production data.

The article does not have specific mention of how the result of the analysis is helping to speed up the process of matchmoving, but we know for sure that something is happening in the field of data and the VFX production process.


Graph source: https://www.foundry.com/trends/business/matchmoving-big-data

However there is one concrete thing I find fascinating in the article. This graph in the article actually gives an overview of the time and resources taken up by each stage in the VFX process.
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