Toby Cabot - Emotion AI Developer Day 2016
•Download as PPTX, PDF•
0 likes•253 views
The document provides an overview of the Android SDK from Affectiva for enabling emotion detection capabilities in Android apps. It describes the callback-oriented architecture where the SDK processes frames and calls back to the app. It also outlines 4 approaches for integrating the SDK: camera-driven, frame-by-frame, processing video files, and processing photos. Finally, it provides guidance on coding a sample camera-driven app using the SDK.
Recommended
Recommended
More Related Content
What's hot
What's hot (11)
Similar to Toby Cabot - Emotion AI Developer Day 2016
Similar to Toby Cabot - Emotion AI Developer Day 2016 (20)
More from Affectiva
Recently uploaded
Recently uploaded (20)
Toby Cabot - Emotion AI Developer Day 2016
- 1. Android SDK Intro Emotion-enable Your Android App Toby Cabot toby.cabot@affectiva.com
- 2. Contents API Architecture 4 Ways to Use the SDK Example Helpful Resources Questions?
- 3. Architecture Callback-oriented: You configure the SDK The SDK calls back when something happens You ask the SDK for the data that you're interested in You stop the SDK
- 4. Control Flow Client SDK Initialization Callback Event Get Data Start Stop ...
- 5. 4 Ways to Use the SDK Camera-driven Client-driven frame-by-frame Pre-recorded video file Pre-recorded photo
- 6. Camera-driven Approach CameraDetector Real-time: frames are processed as they are captured Affdex controls the camera, calls back to client with frame events Easy to use, but less client control
- 7. Frame-by-Frame Client-driven Approach FrameDetector Frames are captured by the client and passed into the SDK Client decides how frames are captured Slightly more complex API, but greater client control
- 8. Processing Files VideoDetector Processes pre-recorded video files (e.g., MP4) Callback-oriented Has inter-frame optimizations for better speed, accuracy PhotoDetector Processes a single frame Callback-oriented
- 9. Coding a CameraDetector App Create a new app in Android Studio Configure Gradle to use the SDK Add a view for the camera Write callback skeletons Configure the detector Implement callbacks
- 10. Helpful Resources Affectiva Developer Portal - http://developer.affectiva.com/ Stack Overflow - http://stackoverflow.com/questions/tagged/affdex-sdk Github - https://github.com/Affectiva?query=android Email - sdk@affectiva.com Android Developer Portal - https://developer.android.com/index.html
Editor's Notes
- The third and fourth approach have to do with processing files: video and photo The VideoDetector is just a convenience wrapper around the FrameDetector. It reads the file frame-by-frame and pushes it into the detector. The key difference between the VideoDetector and the PhotoDetector and is that the VideoDetector has optimizations that can give better results if we get a series of frames that are close together in time (things like looking for faces where we saw them in previous frames).
- Play video here and narrate over it in realtime We go as far back as API 16
- The Developer Portal is the source for Affdex documentation. You can query for answers and ask your own questions on Stack Overflow - just make sure to tag them with the affdex-sdk tag so Affdex-savvy people will pick them up. There are two Android repos on Github: the source to our AffdexMe demo app, and a bunch of simple demos that show all 4 ways to use the SDK. If all else fails send us an email and we'll help.