# Pose On The Go

> Future Interfaces Group CMU

Canonical page: [https://chrome-stats.com/d/id1635810011](https://chrome-stats.com/d/id1635810011)

## Overview

- **ID:** `id1635810011`
- **Platform:** Apple
- **Type:** Apple app
- **Status:** Available
- **Publisher:** Vimal Mollyn
- **Category:** Education
- **Rating:** 5.00 / 5 (2 ratings)
- **Version:** 1.0.0
- **Last updated:** 2022-11-20
- **First published:** 2022-11-16
- **Size:** 287 MB
- **Data as of:** 2026-09-06
- **Store listing:** [Apple App Store](https://apps.apple.com/us/app/pose-on-the-go/id1635810011)
- **Website:** [https://www.figlab.com/research/2021/pose-on-the-go](https://www.figlab.com/research/2021/pose-on-the-go)
- **Privacy policy:** [https://www.figlab.com/research/2021/pose-on-the-go/poseotgprivacypolicy](https://www.figlab.com/research/2021/pose-on-the-go/poseotgprivacypolicy)

## Description

Pose-on-the-Go is a full-body pose estimation system that uses sensors already found in today’s smartphones. This stands in contrast to prior systems, which require worn or external sensors. We achieve this result via extensive sensor fusion, leveraging a phone's front and rear cameras, the user-facing depth camera, touchscreen, and IMU. Even still, we are missing data about a user's body (e.g., angle of the elbow joint), and so we use inverse kinematics to estimate and animate probable body poses. Published at ACM CHI 2021. For more information, check out: https://karan-ahuja.com/poseotg.html

## Rankings

- #634,146 — Overall

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Source: [Chrome-Stats](https://chrome-stats.com/d/id1635810011)