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Agent skill

Egomotion Estimation

by benchflow-ai in benchflow-ai/skillsbench

Estimate camera motion with optical flow + affine/homography, allow multi-label per frame.

Apache-2.0Auto-check passed

Install Egomotion Estimation

skills CLI
$ npx skills add benchflow-ai/skillsbench --skill egomotion-estimation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install benchflow-ai/skillsbench egomotion-estimation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tasks/dynamic-object-aware-egomotion/environment/skills/egomotion-estimation .claude/skills/egomotion-estimation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
egomotion-estimation
GitHub stars
1.8k
Token cost
~502 tokens
SKILL.md length
175 words
Files
1
Skills in repo
178
Repo updated
First seen
Licence
Apache-2.0

At a glance

Estimate camera motion with optical flow + affine/homography, allow multi-label per frame.

  • Works in 5 steps: Feature tracking: goodFeaturesToTrack +… → Robust transform:… → Thresholding (example values) → …
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Egomotion Estimation is an agent skill from benchflow-ai/skillsbench. Estimate camera motion with optical flow + affine/homography, allow multi-label per frame.

Its SKILL.md is about 500 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: SkillsBench evaluates how well skills work and how effective agents are at using them. The licence is Apache-2.0.

Example prompts

  • “/egomotion-estimation”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Feature tracking: goodFeaturesToTrack + calcOpticalFlowPyrLK; drop if too few points.
  2. Robust transform: estimateAffinePartial2D (or homography) with RANSAC to get tx, ty, rotation, scale.
  3. Thresholding (example values)
  4. Temporal smoothing: windowed mode/median to reduce flicker.
  5. Interval compression: merge consecutive frames with identical label sets into start->end.

What it can do on your machine

Read from SKILL.md and the folder at commit 9a1f4dd. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Egomotion Estimation loads about 502 tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 175 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~28
When it runs · the whole SKILL.md, loaded when a task matches
~502

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its Apache-2.0 licence (© benchflow-ai). 175 words, ~502 tokens.

Download SKILL.mdSave it as .claude/skills/egomotion-estimation/SKILL.md (or your agent's skills folder).
name
egomotion-estimation
description
Estimate camera motion with optical flow + affine/homography, allow multi-label per frame.

When to use

  • You need to classify camera motion (Stay/Dolly/Pan/Tilt/Roll) from video, allowing multiple labels on the same frame.

Workflow

  1. Feature tracking: goodFeaturesToTrack + calcOpticalFlowPyrLK; drop if too few points.
  2. Robust transform: estimateAffinePartial2D (or homography) with RANSAC to get tx, ty, rotation, scale.
  3. Thresholding (example values)
    • Translate threshold th_trans (px/frame), rotation (rad), scale delta (ratio).
    • Allow multiple labels: if scale and translate are both significant, emit Dolly + Pan; rotation independent for Roll.
  4. Temporal smoothing: windowed mode/median to reduce flicker.
  5. Interval compression: merge consecutive frames with identical label sets into start->end.

Decision sketch

python
labels=[]
for each frame i>0:
    lbl=[]
    if abs(scale-1)>th_scale: lbl.append("Dolly In" if scale>1 else "Dolly Out")
    if abs(rot)>th_rot: lbl.append("Roll Right" if rot>0 else "Roll Left")
    if abs(dx)>th_trans and abs(dx)>=abs(dy): lbl.append("Pan Left" if dx>0 else "Pan Right")
    if abs(dy)>th_trans and abs(dy)>abs(dx): lbl.append("Tilt Up" if dy>0 else "Tilt Down")
    if not lbl: lbl.append("Stay")
    labels.append(lbl)

Heuristic starting points (720p, high fps; scale with resolution/fps)

  • Tune thresholds based on resolution and frame rate (e.g., normalize translation by image width/height, rotation in degrees, scale as relative ratio).
  • Low texture/low light: increase feature count, use larger LK windows, and relax RANSAC settings.

Self-check

  • Fallback to identity transform on failure; never emit empty labels.
  • Direction conventions consistent (image right shift = camera pans left).
  • Multi-label allowed; no forced single label.
  • Compressed intervals cover all sampled frames; keys formatted correctly.

© benchflow-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in tasks/dynamic-object-aware-egomotion/environment/skills/egomotion-estimation of benchflow-ai/skillsbench.

Open the folder on GitHubat commit 9a1f4dd

Compare with similar skills

Egomotion Estimation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Egomotion Estimation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Egomotion Estimation this skillbenchflow-ai/skillsbench1.8k—~502Automated safety check: PassApache-2.0
HyperFrames Motion Doctrineheygen-com/hyperframes59k1 repos~3kAutomated safety check: PassApache-2.0
Emilkowalski Motionnexu-io/open-design100k—~644Automated safety check: PassApache-2.0
Motion Foundationsaffaan-m/ECC275k1 repos~2.4kAutomated safety check: PassMIT
Motion Patternsaffaan-m/ECC275k1 repos~3.3kAutomated safety check: PassMIT
Motion Advancedaffaan-m/ECC275k1 repos~4.7kAutomated safety check: PassMIT

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Questions about Egomotion Estimation

What does Egomotion Estimation do?

Estimate camera motion with optical flow + affine/homography, allow multi-label per frame. Egomotion Estimation is an agent skill from benchflow-ai/skillsbench. Estimate camera motion with optical flow + affine/homography, allow multi-label per frame.

How do I install Egomotion Estimation in Claude Code?

Run `npx skills add benchflow-ai/skillsbench --skill egomotion-estimation -a claude-code`. Or copy the skill folder (tasks/dynamic-object-aware-egomotion/environment/skills/egomotion-estimation in benchflow-ai/skillsbench) into .claude/skills/egomotion-estimation in your project. Claude Code loads it when a task matches its description.

How do I install Egomotion Estimation in Codex?

Run `npx skills add benchflow-ai/skillsbench --skill egomotion-estimation -a codex`. Or copy the skill folder (tasks/dynamic-object-aware-egomotion/environment/skills/egomotion-estimation in benchflow-ai/skillsbench) into .agents/skills/egomotion-estimation in your project. Codex loads it when a task matches its description.

Can I use Egomotion Estimation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add benchflow-ai/skillsbench --skill egomotion-estimation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/egomotion-estimation, .gemini/skills/egomotion-estimation, .github/skills/egomotion-estimation and .opencode/skills/egomotion-estimation in your project.

What does Egomotion Estimation need to run?

SKILL.md names no scripts, command-line tools or credentials: Egomotion Estimation is instructions for the agent only. Our summary lists: Python 3.

Does Egomotion Estimation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Egomotion Estimation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Egomotion Estimation use?

Egomotion Estimation is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Egomotion Estimation use?

About 502 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Egomotion Estimation?

Skills that share tags, products or a category with Egomotion Estimation: HyperFrames Motion Doctrine (heygen-com/hyperframes, 59k stars), Emilkowalski Motion (nexu-io/open-design, 100k stars), Motion Foundations (affaan-m/ECC, 275k stars) and Motion Patterns (affaan-m/ECC, 275k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Egomotion Estimation?

benchflow-ai (a GitHub organization) maintains it in benchflow-ai/skillsbench, which has 1,832 GitHub stars. The repository holds 178 skills in this directory. The repository was last updated on July 23, 2026.

Source: benchflow-ai/skillsbench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.