author = "Noma, Alexandre and Jr, Roberto Marcondes Cesar",
          affiliation = "{Instituto de Matem{\'a}tica e Estat{\'{\i}}stica - USP} and 
                         {Instituto de Matem{\'a}tica e Estat{\'{\i}}stica - USP}",
                title = "Sparse Representations for Efficient Shape Matching",
            booktitle = "Proceedings...",
                 year = "2010",
               editor = "Bellon, Olga and Esperan{\c{c}}a, Claudio",
         organization = "Conference on Graphics, Patterns and Images, 23. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "point pattern matching, graph matching, quadratic assignment, 
                         Markov random fields, efficient belief propagation, sparse shape 
                         representations, shape metric, 3D object recognition, handwritten 
             abstract = "Graph matching is a fundamental problem with many applications in 
                         computer vision. Patterns are represented by graphs and pattern 
                         recognition corresponds to finding a correspondence between 
                         vertices from different graphs. In many cases, the problem can be 
                         formulated as a quadratic assignment problem, where the cost 
                         function consists of two components: a linear term representing 
                         the vertex compatibility and a quadratic term encoding the edge 
                         compatibility. The quadratic assignment problem is NP-hard and the 
                         present paper extends the approximation technique based on graph 
                         matching and efficient belief propagation described in previous 
                         work by using sparse representations for efficient shape matching. 
                         Successful results of recognition of 3D objects and handwritten 
                         digits are illustrated, using COIL and MNIST datasets, 
                         respectively. .",
  conference-location = "Gramado",
      conference-year = "Aug. 30 - Sep. 3, 2010",
             language = "en",
           targetfile = "paper2.pdf",
        urlaccessdate = "2020, Dec. 05"