Let’s use the example of a bike theft. We enter into evidence a 4-hour security cam video that shows the thief with the bike.
Scenario A: The camera can directly see the bike rack, and the bike in question is visible at the beginning of the video, and not visible at the end. Somewhere in this 4-hour video, someone walks up to the bike and takes it out of the bike rack. You can use a binary search to find the moment that happens in this video because you can pick a frame and say “Ah, this was before the theft; the bike is still there” or “ah, this was after the theft; the bike is gone.”
Scenario B: The camera can’t directly see the bike rack, but can see the doorway you have to walk through to get to the bike rack. So somewhere in 4 hours of doorway footage, someone walks through the door, then a short time later walks back through the door with the bike. A binary search won’t help here because the door looks the same at the beginning or end of the video. A simple binary search won’t work here because the door looks the same before and after.
Scenario B: The camera can’t directly see the bike rack, but can see the doorway you have to walk through to get to the bike rack. So somewhere in 4 hours of doorway footage, someone walks through the door, then a short time later walks back through the door with the bike. A binary search won’t help here
I never said it works 100% of the time. This that it would work most of the time. And I make that statement based on the fact that usually the environment changes around the event, or the event happens long enough to be detectable, if not by humans, then by AI.
In all of my comments I’m assuming that that focal point of the crime is visible.
But even if it wasn’t, if the person stealing the bike knocks over a trash can while doing it and that’s in the camera view it would still be useable. Or if a crowd congregates around the focus point and looks around for the bike, that would also make a binary search feasible.
That’s always just been my point, that a binary surgery more often than not works because most times the environment around the event changes in some way, from subtle to extreme.
You would have to be confident that said change in environment was done by the bike thief. What if that knocked over trash can was done by some unrelated bored teenager twenty minutes after the bike was stolen?
It might be better to use some software to remove any frame of video that is identical to the one before it, no motion is taking place, etc. then manually watch the much shorter video of “only when stuff happens.”
You would have to be confident that said change in environment was done by the bike thief.
Well, the change would happen, the human will be noticed, and then they can watch that moment in time on the tape to see who did it. The binary search would be about shortening what portions of the video tape a human/AI would have to review manually.
It might be better to use some software to remove any frame of video that is identical to the one before it, no motion is taking place, etc. then manually watch the much shorter video of “only when stuff happens.”
So, I hope you’re not under the impression that I’m advocating binary search as the ONLY way of doing a search. I’m just staying within the confines of the subject as brought up by the OP, which was about binary searches.
At the end of the day its about detecting the change/aftereffect, and not the search inandof itself. A binary search just helps you narrow down the video you have to watch manually, especially when there’s allot of it to review.
Let’s use the example of a bike theft. We enter into evidence a 4-hour security cam video that shows the thief with the bike.
Scenario A: The camera can directly see the bike rack, and the bike in question is visible at the beginning of the video, and not visible at the end. Somewhere in this 4-hour video, someone walks up to the bike and takes it out of the bike rack. You can use a binary search to find the moment that happens in this video because you can pick a frame and say “Ah, this was before the theft; the bike is still there” or “ah, this was after the theft; the bike is gone.”
Scenario B: The camera can’t directly see the bike rack, but can see the doorway you have to walk through to get to the bike rack. So somewhere in 4 hours of doorway footage, someone walks through the door, then a short time later walks back through the door with the bike. A binary search won’t help here because the door looks the same at the beginning or end of the video. A simple binary search won’t work here because the door looks the same before and after.
This is the explanation that CosmicCleric needs in order to understand binary search.
Because as it is, (s)he’s failing abysmally at demonstrating any understanding whatsoever of that subject.
I’ve written binary searches before.
I never said it works 100% of the time. This that it would work most of the time. And I make that statement based on the fact that usually the environment changes around the event, or the event happens long enough to be detectable, if not by humans, then by AI.
In all of my comments I’m assuming that that focal point of the crime is visible.
But even if it wasn’t, if the person stealing the bike knocks over a trash can while doing it and that’s in the camera view it would still be useable. Or if a crowd congregates around the focus point and looks around for the bike, that would also make a binary search feasible.
That’s always just been my point, that a binary surgery more often than not works because most times the environment around the event changes in some way, from subtle to extreme.
You would have to be confident that said change in environment was done by the bike thief. What if that knocked over trash can was done by some unrelated bored teenager twenty minutes after the bike was stolen?
It might be better to use some software to remove any frame of video that is identical to the one before it, no motion is taking place, etc. then manually watch the much shorter video of “only when stuff happens.”
Well, the change would happen, the human will be noticed, and then they can watch that moment in time on the tape to see who did it. The binary search would be about shortening what portions of the video tape a human/AI would have to review manually.
So, I hope you’re not under the impression that I’m advocating binary search as the ONLY way of doing a search. I’m just staying within the confines of the subject as brought up by the OP, which was about binary searches.
At the end of the day its about detecting the change/aftereffect, and not the search inandof itself. A binary search just helps you narrow down the video you have to watch manually, especially when there’s allot of it to review.