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With the rise of e-commerce sites like Amazon.com, consumers are increasingly using mobile devices to look up reviews and prices on the Internet before purchasing products in a store. Users appreciate this ability because the extra knowledge gives customers confidence in their purchases. However, obtaining this information is unnecessarily tedious with current technology: customers must either transcribe a product name with a touchscreen keyboard into search a box or take a well framed photo and hope that a visual recognition service correctly determines the product of interest. If there are multiple of objects of interest, the process must be repeated in order to localize each object. We believe this complexity places an unnecessary confusion on the user and diminishes the effectiveness of product identification applications. Therefore, in this project, we seek to develop an interface that allows users to more efficiently identify products of interest by studying, developing, and deploying state-of-the-art visual annotation mechanisms.
GR1 - User and Task Analysis
GR2 - Designs
GR3 - Paper Prototyping
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