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• Vedanti and Max Sound vs. Google

  14 août 2014, par Multimedia Mike — Legal/Ethical

  Vedanti Systems Limited (VSL) and Max Sound Coporation filed a lawsuit against Google recently. Ordinarily, I wouldn’t care about corporate legal battles. However, this one interests me because it’s multimedia-related. I’m curious to know how coding technology patents might hold up in a real court case.

  Here’s the most entertaining complaint in the lawsuit :

  Despite Google’s well-publicized Code of Conduct — “Don’t be Evil” — which it explains is “about doing the right thing,” “following the law,” and “acting honorably,” Google, in fact, has an established pattern of conduct which is the exact opposite of its claimed piety.

  I wonder if this is the first known case in which Google has been sued over its long-obsoleted “Don’t be evil” mantra ?

  Researching The Plaintiffs
  
  I think I made a mistake by assuming this lawsuit might have merit. My first order of business was to see what the plaintiff organizations have produced. I have a strong feeling that these might be run of the mill patent trolls.

  VSL currently has a blank web page. Further, the Wayback Machine only has pages reaching back to 2011. The earliest page lists these claims against a plain black background (I’ve highlighted some of the more boisterous claims and the passages that make it appear that Vedanti doesn’t actually produce anything but is strictly an IP organization) :

  The inventions key :
  The patent and software reduced any data content, without compressing, up to a 97% total reduction of the data which also produces a lossless result. This physics based invention is often called the Holy Grail.

  Vedanti Systems Intellectual Property
  Our strategic IP portfolio is granted in all of the world’s largest technology development and use countries. A major value indemnification of our licensee products is the early date of invention filing and subsequent Issue. Vedanti IP has an intrinsic 20 year patent protection and valuation in royalties and licensing. The original data transmission art has no prior art against it.

  Vedanti Systems invented among other firsts, The Slice and Partitioning of Macroblocks within a RGB Tri level region in a frame to select or not, the pixel.

  Vedanti Systems invention is used in nearly every wireless chipset and handset in the world

  Our original pixel selection system revolutionized wireless handset communications. An example of this system “Slice” and “Macroblock Partitioning” is used throughout Satellite channel expansion, Wireless partitioning, Telecom – Video Conferencing, Surveillance Cameras, and 2010 developing Media applications.

  Vedanti Systems is a Semiconductor based software, applications, and IP Continuations Intellectual Property company.

  Let’s move onto the other plaintiff, Max Sound. They have a significantly more substantive website. They also have an Android app named Spins HD Audio, which appears to be little more than a music player based on the screenshots.

  Max Sound also has a stock ticker symbol : MAXD. Something clicked into place when I looked up their ticker symbol : While worth only a few pennies, it was worth a few more pennies after this lawsuit was announced, which might be one of the motivations behind the lawsuit.

  Here’s a trick I learned when I was looking for a new tech job last year : When I first look at a company’s website and am trying to figure out what they really do, I head straight to their jobs/careers page. A lot of corporate websites have way too much blathering corporatese that can be tough to cut through. But when I see what mix of talent and specific skills they are hoping to hire, that gives me a much better portrait of what the company does.

  The reason I bring this up is because this tech company doesn’t seem to have jobs/careers page.

  The Lawsuit
  The core complaint centers around Patent 7974339 : Optimized data transmission system and method. It was filed in July 2004 (or possibly as early as January 2002), issued in July 2011, and assigned (purchased ?) by Vedanti in May 2012. The lawsuit alleges that nearly everything Google has ever produced (or, more accurately, purchased) leverages the patented technology.

  The patent itself has 5 drawings. If you’ve ever seen a multimedia codec patent, or any whitepaper on a multimedia codec, you’ve seen these graphs before. E.g., “Raw pixels come in here -> some analysis happens here -> more analysis happens over here -> entropy coding -> final bitstream”. The text of a patent document isn’t meant to be particularly useful. I’ve tried to understand this stuff before and it never goes well. Skimming the text, I just see a blur of the words data, transmission, pixel, and matrix.

  So I read the complaint to try to figure out what this is all about. To summarize the storyline as narrated by the lawsuit, some inventors were unhappy with the state of video compression in 2001 and endeavored to create something better. So they did, and called it the VSL codec. This codec is so far undocumented on the MultimediaWiki, so it probably has yet to be seen “in the wild”. Good luck finding hard technical data on it now since searches for “VSL codec” are overwhelmed by articles about this lawsuit. Also, the original codec probably wasn’t called VSL because VSL is apparently an IP organization formed much later.

  Then, the protagonists of the lawsuit patented the codec. Then, years later, Google wanted to purchase a video codec that they could open source and use to supplant H.264.

  The complaint goes on to allege that in 2010, Google specifically contacted VSL to possibly license or acquire this mysterious VSL technology. Google was allegedly allowed to study the technology, eventually decided not to continue discussions, and shipped back the proprietary materials.

  Here’s where things get weird. When Google shipped back the materials, they allegedly shipped back a bunch of Post-It notes. The notes are alleged to contain a ton of incriminating evidence. The lawsuit claims that the notes contained such tidbits as :

  • Google was concerned that its infringement could be considered “recklessness” (the standard applicable to willful infringement) ;
  • Google personnel should “try” to destroy incriminating emails ;
  • Google should consider a “design around” because it was facing a “risk of litigation.”

  Actually, given Google’s acquisition of On2, I can totally believe that last one (On2’s codecs have famously contained a lot of weirdness which is commonly suspected to be attributable to designing around known patents).

  Anyway, a lot of this case seems to hinge on the authenticity of these Post-It notes :

  “65. The Post-It notes are unequivocal evidence of Google’s knowledge of the ’339 Patent and infringement by Defendants”

  I wish I could find a stock photo of a stack of Post-It notes in an evidence bag.

  I’ve worked at big technology companies. Big tech companies these days are very diligent about indoctrinating employees about IP liability issues. The reason this Post-It situation strikes me as odd is because the alleged contents of the notes basically outline everything the corporate lawyers tell you NOT to do.

  Analysis
  I’m trying to determine what specific algorithms and coding techniques. I guess I was expecting to see a specific claim that, “Our patent outlines this specific coding technique and here is unequivocal proof that Google A) uses the same technique, and B) specifically did so after looking at our patent.” I didn’t find that (well, a bit of part B, c.f., the Post-It note debacle), but maybe that’s not how these patent lawsuits operate. I’ve never kept up before.

  Maybe it’s just a patent troll. Maybe it’s for the stock bump. I’m expecting to see pump-n-dump stock spam featuring the stock symbol MAXD anytime now.

  I’ve never been interested in following a lawsuit case carefully before. I suddenly find myself wondering if I can subscribe to the RSS feed for this case ? Too much to hope for. But I found this item through Pando and maybe they’ll stay on top of it.

• Visualizing Call Graphs Using Gephi

  1er septembre 2014, par Multimedia Mike — General

  When I was at university studying computer science, I took a basic chemistry course. During an accompanying lab, the teaching assistant chatted me up and asked about my major. He then said, “Computer science ? Well, that’s just typing stuff, right ?”

  My impulsive retort : “Sure, and chemistry is just about mixing together liquids and coming up with different colored liquids, as seen on the cover of my high school chemistry textbook, right ?”

  
  
  

  In fact, pure computer science has precious little to do with typing (as is joked in CS circles, computer science is about computers in the same way that astronomy is about telescopes). However, people who study computer science often pursue careers as programmers, or to put it in fancier professional language, software engineers.

  So, what’s a software engineer’s job ? Isn’t it just typing ? That’s where I’ve been going with this overly long setup. After thinking about it for long enough, I like to say that a software engineer’s trade is managing complexity.

  A few years ago, I discovered Gephi, an open source tool for graph and data visualization. It looked neat but I didn’t have much use for it at the time. Recently, however, I was trying to get a better handle on a large codebase. I.e., I was trying to manage the project’s complexity. And then I thought of Gephi again.

  Prior Work
  One way to get a grip on a large C codebase is to instrument it for profiling and extract details from the profiler. On Linux systems, this means compiling and linking the code using the -pg flag. After running the executable, there will be a gmon.out file which is post-processed using the gprof command.

  GNU software development tools have a reputation for being rather powerful and flexible, but also extremely raw. This first hit home when I was learning how to use the GNU tool for code coverage — gcov — and the way it outputs very raw data that you need to massage with other tools in order to get really useful intelligence.

  And so it is with gprof output. The output gives you a list of functions sorted by the amount of processing time spent in each. Then it gives you a flattened call tree. This is arranged as “during the profiled executions, function c was called by functions a and b and called functions d, e, and f ; function d was called by function c and called functions g and h”.

  How can this call tree data be represented in a more instructive manner that is easier to navigate ? My first impulse (and I don’t think I’m alone in this) is to convert the gprof call tree into a representation suitable for interpretation by Graphviz. Unfortunately, doing so tends to generate some enormous and unwieldy static images.

  Feeding gprof Data To Gephi
  I learned of Gephi a few years ago and recalled it when I developed an interest in gaining better perspective on a large base of alien C code. To understand what this codebase is doing for a particular use case, instrument it with gprof, gather execution data, and then study the code paths.

  How could I feed the gprof data into Gephi ? Gephi supports numerous graphing formats including an XML-based format named GEXF.

  Thus, the challenge becomes converting gprof output to GEXF.

  Which I did.

  Demonstration
  I have been absent from FFmpeg development for a long time, which is a pity because a lot of interesting development has occurred over the last 2-3 years after a troubling period of stagnation. I know that 2 big video codec developments have been HEVC (next in the line of MPEG codecs) and VP9 (heir to VP8’s throne). FFmpeg implements them both now.

  I decided I wanted to study the code flow of VP9. So I got the latest FFmpeg code from git and built it using the options "--extra-cflags=-pg --extra-ldflags=-pg". Annoyingly, I also needed to specify "--disable-asm" because gcc complains of some register allocation snafus when compiling inline ASM in profiling mode (and this is on x86_64). No matter ; ASM isn’t necessary for understanding overall code flow.

  After compiling, the binary ‘ffmpeg_g’ will have symbols and be instrumented for profiling. I grabbed a sample from this VP9 test vector set and went to work.

  ./ffmpeg_g -i vp90-2-00-quantizer-00.webm -f null /dev/null
  gprof ./ffmpeg_g > vp9decode.txt
  convert-gprof-to-gexf.py vp9decode.txt > /bigdisk/vp9decode.gexf
  

  Gephi loads vp9decode.gexf with no problem. Using Gephi, however, can be a bit challenging if one is not versed in any data exploration jargon. I recommend this Gephi getting starting guide in slide deck form. Here’s what the default graph looks like :

  
  
  

  Not very pretty or helpful. BTW, that beefy arrow running from mid-top to lower-right is the call from decode_coeffs_b -> iwht_iwht_4x4_add_c. There were 18774 from the former to the latter in this execution. Right now, the edge thicknesses correlate to number of calls between the nodes, which I’m not sure is the best representation.

  Following the tutorial slide deck, I at least learned how to enable the node labels (function symbols in this case) and apply a layout algorithm. The tutorial shows the force atlas layout. Here’s what the node neighborhood looks like for probing file type :

  
  
  

  Okay, so that’s not especially surprising– avprobe_input_format3 calls all of the *_probe functions in order to automatically determine input type. Let’s find that decode_coeffs_b function and see what its neighborhood looks like :

  
  
  

  That’s not very useful. Perhaps another algorithm might help. I select the Fruchterman–Reingold algorithm instead and get a slightly more coherent representation of the decoding node neighborhood :

  
  
  

  Further Work
  Obviously, I’m just getting started with this data exploration topic. One thing I would really appreciate in such a tool is the ability to interactively travel the graph since that’s what I’m really hoping to get out of this experiment– watching the code flows.

  Perhaps someone else can find better use cases for visualizing call graph data. Thus, I have published the source code for this tool at Github.

• Revision bb4950dfdf : vp9 : correct context buffer resize check allocations within vp9_alloc_context_b

  5 septembre 2014, par James Zern

  Changed Paths :
   Modify /test/invalid_file_test.cc

  
   Modify /test/test-data.sha1

  
   Modify /test/test.mk

  
   Modify /vp9/decoder/vp9_decodeframe.c

  
  
  vp9 : correct context buffer resize check

  allocations within vp9_alloc_context_buffers() rely on mi_rows/mi_cols
  individually, use those to determine whether to realloc rather than
  stride and stride * rows. this fixes a crash with some fuzzed files for
  invalid accesses into last_frame_seg_map and above_context.

  Change-Id : I7b9f40dcf170d443890f3bd2acd285507943c7d4