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Maintaining an accurate and up-to-date inventory of one's assets is a labor-intensive, tedious, and costly operation.
To ease this difficult but important task, we design and implement a mobile asset tracking system for
automatically generating an inventory by snapping photos of the assets with a smartphone. Since smartphones
are becoming ubiquitous, construction and deployment of our inventory management solution is simple and costeffective.
Automatic asset recognition is achieved by first segmenting individual assets out of the query photo
and then performing bag-of-visual-features (BoVF) image matching on the segmented regions. The smartphone's
sensor readings, such as digital compass and accelerometer measurements, can be used to determine the location
of each asset, and this location information is stored in the inventory for each recognized asset.
As a special case study, we demonstrate a mobile book tracking system, where users snap photos of books
stacked on bookshelves to generate a location-aware book inventory. It is shown that segmenting the book spines
is very important for accurate feature-based image matching into a database of book spines. Segmentation
also provides the exact orientation of each book spine, so more discriminative upright local features can be
employed for improved recognition. This system's mobile client has been implemented for smartphones running
the Symbian or Android operating systems. The client enables a user to snap a picture of a bookshelf and to
subsequently view the recognized spines in the smartphone's viewfinder. Two different pose estimates, one from
BoVF geometric matching and the other from segmentation boundaries, are both utilized to accurately draw the
boundary of each spine in the viewfinder for easy visualization. The BoVF representation also allows matching
each photo of a bookshelf rack against a photo of the entire bookshelf, and the resulting feature matches are
used in conjunction with the smartphone's orientation sensors to determine the exact location of each book.
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