Are there video "thumbprints" like exists for audio (used by soundhound/etc) - IE a compressed set of features that can reliably be linked in unique content? I would expect that is possible and a lot faster lookup for 2 frames a second. If this is the case, the "your device is taking a snapshot every 30 seconds" sounds a lot worse (not defending it - it's still something I hope can be legislated away - something can be bad and still exaggerated by media)

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woodson 17 hours ago | parent | next [-]

There are perceptual hashing algorithms for images/video/audio (dsp and ML based) that could work for that.

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tshaddox 16 hours ago | parent [-]

Given that the TV is trying to match one digital frame against another digital frame, you could probably get decent results even with something super naive like downsampling to a very low resolution, quantizing the color palette, then looking for a pixel for pixel match.

All this could be done long before any sort of TV-specific image processing, so the only source of "noise" I can think of would be from the various encodings offered by the streaming service (e.g. different resolutions and bitrates). With the right choice of downsample resolution and color quantization I have to imagine you could get acceptable results.

	▲	paradox460 15 hours ago \| parent [-]
		That's basically what phash does

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Rediscover 15 hours ago | parent | prev [-]

I've been led to believe those video thumbprints exist, but I know the hash of the perceived audio is often all that is needed for a match of what is currently being presented (movie, commercial advert, music-as-music-not-background, ...).

	▲	lurk2 6 hours ago \| parent [-]
		This is why a lot of series uploaded to YouTube will be sped up, slowed down, or have their audio’s pitch changed; if the uploader doesn’t do this, it gets recognized by YouTube as infringing content.