Efficient alignment for vehicle make and model recognition
This paper presents a make and model recognition system for passenger vehicles. We propose a two-step efficient alignment mechanism to account for view point changes. The 2D alignment problem is solved as two separate one dimensional shortest path problems. To avoid the alignment of the query with the entire database, reference views are used. These views are generated iteratively from the database. To improve the alignment performance further, use of two references is proposed: a universal view and type specific showcase views. The query is aligned with universal view first and compared with the database to find the type of the query. Then the query is aligned with type specific showcase view and compared with the database to achieve the final make and model recognition. We report results on database of 1500 vehicles with more than 250 makes and models.