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Eric Minner & James Pittman. Outline Project Statement / Motivation Concept overview Quick computer vision overview Demo Lessons Learned Future Work.

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Presentation on theme: "Eric Minner & James Pittman. Outline Project Statement / Motivation Concept overview Quick computer vision overview Demo Lessons Learned Future Work."— Presentation transcript:

1 Eric Minner & James Pittman

2 Outline Project Statement / Motivation Concept overview Quick computer vision overview Demo Lessons Learned Future Work

3 Project Description Participatory sensing often relies on receiving a great number of varied inputs to provide a useful service. The goal of the project is to design a system concept that will find novel images in the world. This system needs to have a way to help encourage a stream of interesting and novel shots.

4 Concept Overview Leverage existing mobile phone capture and image transfer protocols to allow users to submit images. Setup a backend server using apache, and a website to host “novel photo of the day” Use a computer vision algorithm to parse the submitted images and create a ranking scheme to encourage further participation for users to submit images

5 Concept Diagram Camera capture w/EMAIL or other image transfer protocol Mobile Phone or Emulator Image Database Apache Server HTML & PHP source for “picture of the day” website Backend Java Application for image processing and ranking WWW Backend PC GMAIL Server Email Retrieval Application (Outlook) Image Metric Files

6 Image Flow Wait for Image Image Received from Email Java App detects new Image Extract Image Features Compare against database Accumulate Similarity measure Generate new image IMF Update database IMFs Add to database Update Database Hierarchy Update Webpage Has the novel image changed? N Y

7 Demo

8 Lessons Learned 1. Choosing non subjective features for images is very hard. When you automatically rank images based on a feature type you won’t always get the result that visually you think you should 2. Large images (1MB or larger) take forever to send to the server. We need something to handle memory size scaling (the iPhone has this built in, but not all devices do) 3. Resolution scaling (for proper display on the site) was an issue and currently we just force all the images to the same size

9 Future Work 1. Integrate the image capture and submission into a mobile phone application 2. Improve image scoring / feedback process to users by having the system return a ranking directly to the user either via email/SMS or as part of the application 3. Adapt system to work with other types of participatory sensing (such as: fuel prices or carbon footprint tracking) 4. Image scaling / compression when received by email


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