Guide · Pillar

How to Search Video Footage: Seven Ways to Find the Shot in Your Head

You already know something about the shot you want. This guide turns whatever you remember, a line of dialogue, a face, a colour, a feeling, into a query that finds it.

6 min read

Every search starts with something you already know. A line somebody said. A face. A colour you remember. The fact that it was the wide one, shot on the second day, before lunch.

The mistake is trying to convert that into a filename. You end up guessing at the shorthand your past self used at 2am, and that shorthand was never a description of the shot in the first place.

FrameQuery lets you search from whatever fragment you actually kept. This guide covers seven ways in, when each is the right tool, and what to type.

What you rememberWhat to doExample
The exact words somebody saidQuote them"we should push the launch"
Roughly what was said, not the wordsDescribe it in plain languagetalking about delaying the launch
Who is in itName them@sarah
What is physically in shotName the thingwhiteboard
What the shot feels likeDescribe the mood and lightquiet empty office at dusk
How it was framed or shotUse a filtershot:wide angle:eye-level
Only the file nameType it as-isA001_C012
Nothing, but you have one good shotOpen it and use Find Similarno typing at all
Start from what you already know, not from what the tool can do

Search what was said

Every indexed clip has a transcript with sentence-level timestamps, so a dialogue search does not just tell you which file. Each result carries the timecode of the line that matched, and clicking it takes you there.

Type the words plainly and you get clips containing all of them, anywhere in the clip, in any order. Put quotes around them and you only get clips where those words appear together, in that order.

You want

The bit where the CEO said the launch was slipping

Type

"push the launch"

Without quotes you also get every clip that mentions a launch and separately mentions pushing. With quotes you get the sentence.

You want

Any discussion of the budget, no matter how it was phrased

Type

budget

Unquoted single words are the right tool when you want breadth. Start here, then narrow.

You want

The soundbite, but only from the interview, not the panel

Type

"we had to start over" -panel

The exclusion strips the coverage you already know you do not want.

Quotes are the difference between browsing and finding

The rule of thumb: quote when you are sure of the wording, do not quote when you are sure of the topic. Most wasted searching comes from quoting a half-remembered phrase. If you are not certain of the exact words, the next section is what you want instead.

Search what was meant

You remember the gist of what someone said, not the sentence. Quoting will fail here, and so will keywords, because people rarely use the word you are thinking of.

Describe it instead. talking about leaving her job finds a clip where someone said "I handed in my notice in March", even though the words do not overlap at all. Meaning is matched, not spelling.

You want

Someone explaining why the project nearly failed

Type

explaining what went wrong with the project

Matches the sense of a passage. The speaker never has to use the word "failed".

You want

The moment somebody thanks their family

Type

thanking their parents

Works on "I owe all of this to my mum and dad" with no shared vocabulary at all.

You want

Anything where a person sounds unsure about a decision

Type

hesitant about making a decision

Tone and stance, not keywords. This is the search that keyword tools cannot do.

Describe the substance. Do not try to guess the words.

A useful habit

Write the query as if you were describing the clip to an assistant editor over the phone. Full sentences work better than keyword soup, because you are matching meaning and a longer phrase carries more of it.

Search who is in it

Name a person once and they become searchable everywhere. Type @ and the name, and you get every clip where they appear on screen or speak.

That second half matters more than it sounds. A search for @sarah returns the clip where Sarah is talking off camera while someone else is in frame. Face-only tools miss those, and they are frequently the ones you need.

You want

Everything with Sarah in it

Type

@sarah

On screen or on mic. Use quotes for a full name: @"Sarah Chen".

You want

Sarah talking about the merger specifically

Type

@sarah "the merger"

A person plus a phrase is the highest-yield combination in the whole grammar.

You want

The two of them in the same shot

Type

@sarah @james

Two-hander coverage, found in one query instead of scrubbing for it.

You want

James, but not the town hall footage

Type

@james -town-hall

Recurring events dominate a person's results. Subtract the one you are not after.

The @ operator narrows any other search to one person

Naming happens in the People tab of the manager, not in the search results. Turn on biometric analysis, add a person, and assign the detected faces and voices to them. You can also right-click a speaker tag in a clip's transcript panel to name whoever is talking. It takes a couple of minutes per project and every @ search afterwards depends on it.

The deep dive on finding people across your footage walks through that setup and what to do when somebody's results look thin.

Search what is on screen

Objects are detected per scene, so you can search for a thing rather than a description of a thing. whiteboard, bicycle, laptop, dog. This is what covers footage with no dialogue at all: drone plates, B-roll, timelapses, cutaways.

It is also the fastest way to answer a producer's question. "Do we have anything with a coffee cup in it" is a five second search rather than an afternoon.

You want

Cutaways to use over a voiceover about the office

Type

laptop keyboard desk

Several object terms broaden the net. Any of them appearing is a hit.

You want

Product shots without anyone holding it

Type

bottle -hands

Excluding an object is an underused way to control the composition of your results.

You want

Every shot with a vehicle in it, from a mixed library

Type

car van truck

Objects work on footage that has no transcript, which is where filename search dies.

Objects are literal. Say the thing, not the vibe.

Search the feel of a shot

This is the one people do not expect to work. You can search the frame itself, with a description of what it looks and feels like, and get matches even where no description or transcript exists.

empty street at dawn. harsh fluorescent office lighting. crowd shot, hands in the air. quiet and cold. You are describing an image, and images are matched directly against your words.

You want

An establisher that feels lonely

Type

empty landscape under grey sky

Light, space and weather are all things the frame carries and nobody writes down.

You want

Something warm to cut to after a hard scene

Type

golden hour, backlit, people laughing

Combining colour temperature with an action gets you much closer than either alone.

You want

The claustrophobic interview setup, not the airy one

Type

tight framing against a dark wall

Framing plus environment. This is the search that replaces scrubbing through dailies.

Mood searches. Vague is fine here, as long as it is visual.

Short for browsing, long for finding

A single feeling word works. Type peaceful and you get the calmer end of your library, which is exactly right when you are looking for something rather than for one thing. When you need a specific shot, lengthen it instead of rephrasing: still water at sunrise, no people. Both are valid, they just answer different questions.

The deep dive on searching by look, mood and framing goes through colour, shot type and camera angle properly.

Search how it was shot

Sometimes the content is irrelevant and the specification is everything. You need the 4K material, or the ProRes, or everything from the second camera, or only the slow motion.

Filters use field:value and stack freely with everything else.

FieldValuesWhat it is for
codec:prores, braw, r3d, h264, hevc, dnxhrPull only the format you can cut natively today.
res:or resolution:4k, 1080p, 8kFind the deliverable-grade material in a mixed library.
camera:any make or model in the file metadataSeparate A-cam from the crash cam or the drone.
fps:24, 25, 50, 120The fastest way to isolate slow-motion coverage.
container:mov, mp4, mxfUseful when the same shot exists as both original and proxy.
lens:any lens recorded by the cameraMatch coverage shot on the same glass.
iso:800, 3200Track down the shots that will be noisy before you grade them.
date:a shoot dateScope to a single day of a multi-day shoot.
tc:or timecode:a timecode valueJump to a logged moment from a paper edit.
shot:or shot_type:wide, medium-wide, close-up, extreme-close-upAsk for framing rather than content. Hyphenated, though spaces and underscores are accepted.
angle:or shot_angle:eye-level and other hyphenated anglesFind the cutaway that matches your master's eyeline.
Filter fields. Type them as field:value, or use quotes for multi-word values.

You want

Only the slow-motion coverage from the A camera

Type

fps:120 camera:FX9

Two filters, no search terms at all. A perfectly valid query.

You want

Wide shots to open the sequence, in a cuttable format

Type

shot:wide codec:prores

Framing plus format. This is a shot-selection query, not a content query.

You want

The low-angle hero shots of the building

Type

building shot:wide angle:eye-level

Filters narrow, the plain term supplies the subject. Mix them freely.

You want

Deliverable-grade material only, from one shoot day

Type

res:4k date:2026-05-14

Turns a mixed archive into just the material you are allowed to use.

Filters combine with each other and with plain search terms

Combine, then subtract

Every one of the above composes. The queries that actually save you time are almost never a single term.

A useful pattern is to go wide, look at what you got, then subtract. Adding terms narrows on content. Subtracting terms removes the specific category of result that keeps showing up and wasting your attention.

"exact phrase"

Exact phrase

Only matches when those words appear together, in that order.

"final cut"

@name

Person

Narrows to a person you have named, whether they are on screen or speaking.

@sarah or @"Sarah Chen"

-word

Exclude

Removes results containing that word. Works on phrases too.

-rehearsal or -"work in progress"

field:value

Filter

Restricts by a technical or shot property. Combine as many as you like.

codec:prores shot:wide

plain words

Meaning

No operator at all. Describe what you are after and every layer is searched at once.

someone looking nervous before going on stage

The full query grammar. Everything else is plain description.

Worked example. You want the moment your founder talks about the early days, from an interview, not from a conference stage, in wide framing so it cuts against the close-ups you already have:

@maya "when we started" shot:wide -conference -stage

That is a person, an exact phrase, a framing filter and two exclusions in one line. Typing it takes fifteen seconds. Finding that clip by scrubbing takes the rest of the morning.

Read the badge to learn what your library knows

Every result carries a badge saying which layer matched it. It is easy to ignore, and it is the fastest way to get better at searching.

transcriptWhat was said

The words in the spoken audio, timestamped to the moment they were said.

e.g. we should push the launch to Q3

sceneWhat was happening

A written description of each scene, so you can search editorial context rather than keywords.

e.g. two people shaking hands in a lobby

visualWhat the frame looks like

The image itself, matched against your words directly. No description has to exist first.

e.g. moody neon alleyway at night

objectWhat is in shot

Individual things detected in the frame, listed per scene.

e.g. whiteboard

metadataHow it was shot

Camera, codec, resolution, frame rate, lens, ISO, timecode and date, read from the file.

e.g. camera:FX9 res:4k

filenameWhat it is called

The literal file name, for when a DIT hands you a card number and nothing else.

e.g. A001_C012

Every result carries a badge naming the layer that found it

If your results are all filename, your query is only matching file names, which means the description you typed is not landing. If they are all transcript when you wanted visuals, you are describing what people say instead of what the camera sees. The badge tells you which knob to turn.

When a search comes back wrong

Almost every empty or useless result set has one of a small number of causes.

Nothing at all, for a phrase you are certain about

Quotes demand an exact, in-order match, and transcripts vary on filler words and contractions. Drop the quotes and let the meaning match do the work.

Trypush the launch

Nothing at all, for footage you know you have

You are probably scoped to one project. The toggle beside the search bar switches between This project and All projects whenever a project is selected.

Trysame query, set to All projects

A person returns far fewer clips than expected

Their faces or voices are sitting in more than one identity. Open the People tab, assign the leftover identities to them, or use Merge With to fold a duplicate person in.

Try@sarah, after merging

Results are technically right but all from one shoot

One dominant event is crowding everything else out. Subtract it and see what is underneath.

Tryinterview -"town hall"

Every result is a filename match

Your terms are not matching content. Rewrite the query as a description of what happens in the shot rather than a label for it.

Trytwo people talking across a desk

A mood search is in the right mood but too broad

A single feeling word is a browsing query and it is doing its job. To narrow it, add what the shot physically contains rather than swapping the word.

Tryperson alone at a window, low light

A filter silently kills the query

Filter values must exist in the footage. If no clip is tagged close-up, shot:close-up returns nothing. Remove the filter and check the results carry that property at all.

Tryclose on hands

When a search comes back wrong, one of these is almost always why

When you cannot describe it at all

Sometimes you know the shot when you see it and cannot get within a mile of it in words. There is a way around that. Find one result that is close and use Find similar scenes on it.

Instead of matching your words, it matches the shot. You get scenes that share its content and its look. There is a Find similar lines alongside it for transcripts, so you can take one good soundbite and pull every other moment where somebody said something like it.

Use it when a search gets you to roughly the right place. The second hop from a near-miss is usually shorter than any amount of rephrasing.

Build the habit

Three things separate people who find footage quickly from people who scrub.

Name your people early. A few minutes in the People tab on a new project turns @ into the most valuable operator in the grammar for the entire life of that footage.

Search descriptions, not labels. The instinct from twenty years of file browsers is to type the shorthand you would have written on a folder. Type what a stranger would see instead.

Subtract more than you add. When the results are wrong rather than empty, exclusion nearly always fixes it faster than another search term.

Once you have those, the rest is knowing which of the seven doors to walk through, and the table at the top of this guide covers that at a glance.

Common questions

What is the best way to search video footage when you only half remember the shot?
Describe it in plain language rather than guessing at keywords. FrameQuery searches spoken words, scene descriptions, detected objects and the frames themselves at the same time, so a sentence like 'someone laughing at a kitchen table' can match footage that was never tagged or transcribed with any of those words.
Can you search video by what someone said?
Yes. Every indexed clip is transcribed with sentence-level timestamps, so each result carries the timecode of the line that matched and you land on the moment the phrase was spoken rather than the top of the file. Put the words in quotes for an exact phrase, or describe the gist without quotes to match the meaning instead.
How do you find every clip a particular person appears in?
Add the person once in the People tab and assign their detected faces and voices to them, then search @theirname. FrameQuery matches both faces on screen and voices in the audio, so the results include clips where they speak off camera as well as clips where they are visible.
Why does a video search return no results?
Usually one of four reasons: the footage has not finished indexing, the query is in quotes and the exact phrase never occurs, an excluded term is removing more than you expect, or you are scoped to one project instead of the whole library. Widen the scope first, then drop the quotes.
Can you search video without an internet connection?
Yes. Indexing needs a connection, but once a clip is indexed its search data lives on your machine. Searching runs locally with no network round trip and no per-query cost.

Try it on your own footage

Index a folder and search it the way this guide describes. Searching your library is free and works offline once indexing is done.