Tree based object matching using multi-scale covariance descriptor

Object matching is the process of determining the presence and the location of a reference object inside a scene image. Matching accuracy requires robust image description and efficient similarity measures. In this paper, we present a tree based object matching approach using a descriptor proposed in a previous work [1]. Visual objects are described by a collection of multi-scale covariance matrices structured in a tree form. Tree matching is then performed to match visual objects. With this approach, matching accuracy considerably increases compared to traditional image matching techniques. The proposed matching approach is evaluated on CAVIAR dataset. Overall, our approach is an important contribution to a complete system for object reidentification and tracking over different camera views.