Caterpie -- Detect Face and Emotion in Picture and Video

CSC 495/588 2016-Fall Final Project.

Due on:12/08/2016

Caterpie

  • Face API Key 0:
    3289657d188b4159b39df028555c5a19
  • Face API Key 1:
    53f0f8e7b089401db3d4489ecce67957
  • Emotion API Key 0:
    dad2de94aee4433d82c6b0a794e3c9c4
  • Emotion API Key 1:
    a97a8e90bb1a49bf8c03b8bd55eefc10

Background

Caterpie

In this project, we consider the problem of detecting people's faces and their emotions, including happiness, sadness, surprise, anger, contempt, fear, disgust and indifference/neutral. This has several useful industry applications, including aggregating and analyzing reactions of people attending an event. For this project, we use Microsoft Azure Cognitive Service to study how to construct and implement a face and emotion detection api.
Our project contains two parts: Face Detection and Emotion Detection.

Objectives and Targets

  • Detect face positions from the image using Face API.
  • Detect face emotions from the image using Emotion API.
  • Extract face bounding boxes and emotions from video content instead of image (MP4, MOV, or WMV file)

Submission

Your submission should include:

  1. A detailed project report to describe what you have done, including screenshots and code snippets. You also need to provide explanation to the observations that are interesting or surprising. You are encouraged to pursue further investigation, beyond what is required by the project description. Your can earn bonus points for extra efforts.
  2. Your program source files in any programming language you like. Note: *DO NOT* submit your binary result or raw data files.
No copy or cheating is tolerated. If your work is based on others', please give clear attribution. Otherwise, you WILL FAIL this course.

How to submit:

You can either create a github project page (highly recommend) and submit the project URL or you can submit through D2L system.

Tutorials and Supporting Materials