A heuristic for the retrieval of objects in low resolution video

International audienceIn this paper, we tackle the problem of matching of objects in video in the context of the rough indexing paradigm. In this context, the video data are of very low resolution and segmentation is consequently inaccurate. The region features (texture, color, shape) are not strongly relevant due to the resolution. The structure of the objects must be considered in order to improve the robustness of the matching of regions. Indeed, the problem of object matching can be expressed in terms of directed acyclic graph (DAG) matching. Here, we propose a method based on a heuristic in order to approach object matching. The results are compared with those of a method based on relaxation matching

On an Algorithm of Zemlyachenko for Subtree Isomorphism

Zemlyachenko's linear time algorithm for free tree isomorphism is unique in that it also partitions the set of rooted subtrees of a given rooted tree into isomorphism equivalence classes. Unfortunately, his algorithm is very hard to follow. In this note, we use modern data structures to explain and implement Zemlyachenko's scheme. We give a full description of a free rendition of his method using some of his ideas and adding some new ones; in particular, the data structures are new. email: fdititz, itai, [email protected] 1 1 Introduction Free tree isomorphism is a well known problem which has many applications. A linear time algorithm to solve the problem has been developed by Hopcroft and Tarjan [2], who used it to devise a linear planarity test. Several other linear algorithms were suggested [1, pp.196-199], [3], [4]. The common approach is as follows. First, free tree isomorphism is reduced to the rooted case. The root is set canonically at the central vertex or at the ..