Monday, October 11, 2010

Reading #12: Constellation models

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  • Sharon describes a system of Constellation Models for Sketch Recognition. Constellation models describe sketches by the relationships between various objects. The objects themselves are recognized using very simple features: the bounding box position, diagonal length, and angle. Interactions between objects are also described with very simple features: the distance between the centers of the strokes, the shortest distance between any two endpoints and the shortest distance between any two points.

    The feature vectors are used in a ML search through the space of possible labellings to find the assignment of labels to strokes that maximizes the probability of the labeling being correct given the training data. The search is broken into two steps: required components and then optional components, which drastically improves the search time. Separating the search into two steps drastically reduces the search space, by reducing the potential number of labels and also the number of candidate strokes.

    I think this is a really neat approach. With respect to the current assignment, it would be pretty cool to break course of action diagrams into components like this. For example, to identify the echelon modifier and the strength modifier.

    This approach is also somewhat similar to LADDER in that it is very important where objects are in relation to the other objects in the sketch. For example, a right eye will never be on the wrong side of the left eye. These constraints are not modeled explicitly, but are learned from the training data. The constellation model only understands positional relationships, as opposed to LADDER, which can model more complex relationships like parallel-ness.

    2 comments:

    1. This paper brings up some interesting parameters, namely the relationship between different strokes. We used this in our truss recognizer, but it's nice to see this sort of thing generalized. And you're right about the second assignment; I think we can use [parts of] this algorithm used in the 2nd homework assignment.

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    2. I'm still not sure how well this constrains go with the concept of freehand sketching!

      Is this sort of a way of restricting users to draw a certain shape based on the authors standpoint? Correct me if I'm wrong....

      I guess we can create a nice family of constellation models for the COA digram recognition system......I had the same idea when reading the paper......

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