Disclosure certainty 4/5 debate potential 1/5

Dextro uses a salience graph to measure video concept prominence

David Luan · David Luan, Dextro // Real-World Video Understanding (FirstMark / Data Driven NYC) · May 28, 2015 · at 1:44

David Luan, co-founder of video computer vision startup Dextro, explains how their platform analyzes and summarizes video streams at Data Driven NYC in May 2015.

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“So what we do is we provide what's, what's also a salience graph, which is a discounted score of how important every concept Or how prominent a particular category is over the video as a whole. So it's not a measure of our confidence, but of actually how important was this theme over the course.”

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More from David Luan

Assertion Supported
Dextro was the first to offer automated video analysis as a service
“We were the first company to figure out how to get this level of analysis of what's happening in videos as a service.”
David Luan May 28, 2015 ▶ 3:01 David Luan, Dextro // Real-World Video Understanding (FirstMark / Data Driven NYC)
Opinion
Academic reviewers are tired of papers blindly applying deep learning
“And I think the reviewers now are pretty tired of that and they're moving on, but.”
David Luan May 28, 2015 ▶ 7:34 David Luan, Dextro // Real-World Video Understanding (FirstMark / Data Driven NYC)
Insight
Enterprise customers will not pay for 80% accurate machine learning
“But in most cases, customers aren't willing to pay for a product that only gets them 80% of the way. You have to kind of like specialize and focus on the problem to make sure that you get to being 100%.”
David Luan May 28, 2015 ▶ 8:44 David Luan, Dextro // Real-World Video Understanding (FirstMark / Data Driven NYC)
Disclosure
Dextro analyzes video strictly through computer vision, not metadata
“This is all just done with computer vision. We don't use any of the metadata whatsoever to identify what's actually happening.”
David Luan May 28, 2015 ▶ 3:55 David Luan, Dextro // Real-World Video Understanding (FirstMark / Data Driven NYC)
Insight
Models trained on stock images fail to generalize to real-world video
“Classifiers that are and models that are trained in tune on this particular, on iconic type of data don't really generalize as well when you apply it to something that you might see in a real-world video like on YouTube or on Periscope.”
David Luan May 28, 2015 ▶ 10:38 David Luan, Dextro // Real-World Video Understanding (FirstMark / Data Driven NYC)
Insight
Frame-level tags lack the high-level semantic context required for video discovery
“Video or frame-level tags, the sort that you might see on, that I've put on the screen right now, didn't actually solve their problem. Because that was, it was too low level in like a, in a, in not in terms of a granularity sense, but in terms of how much addi…”
David Luan May 28, 2015 ▶ 11:05 David Luan, Dextro // Real-World Video Understanding (FirstMark / Data Driven NYC)
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