Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient Hierarchical Graph-Based Segmentation of RGBD Videos   We present an efficient and scalable algorithm for segmenting 3D RGBD point
clouds by combining depth, color, and temporal information using a multistage,
hierarchical graph-based approach. Our algorithm processes a moving window over
several point clouds to group similar regions over a graph, resulting in an
initial over-segmentation. These regions are then merged to yield a dendrogram
using agglomerative clustering via a minimum spanning tree algorithm. Bipartite
graph matching at a given level of the hierarchical tree yields the final
segmentation of the point clouds by maintaining region identities over
arbitrarily long periods of time. We show that a multistage segmentation with
depth then color yields better results than a linear combination of depth and
color. Due to its incremental processing, our algorithm can process videos of
any length and in a streaming pipeline. The algorithm's ability to produce
robust, efficient segmentation is demonstrated with numerous experimental
results on challenging sequences from our own as well as public RGBD data sets.

10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int