In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …

Optimization is a powerful paradigm for expressing and solving problems in a wide range of
areas, and has been successfully applied to many vision problems. Discrete optimization …

Function and shape data analysis are old topics in statistics, studied off and on over the last
several decades. However, the early years of the new millennium saw a renewed focus and …

This paper introduces a square-root velocity (SRV) representation for analyzing shapes of
curves in euclidean spaces under an elastic metric. In this SRV representation, the elastic …

Part structure and articulation are of fundamental importance in computer and human vision.
We propose using the inner-distance to build shape descriptors that are robust to articulation …

Empirical evaluation of salient object segmentation methods requires i) a dataset of ground
truth object segmentations and ii) a performance measure to compare the output of the …

This paper presents a novel framework for the recognition of objects based on their
silhouettes. The main idea is to measure the distance between two shapes as the minimum …

We propose EMD-L_ {1}: a fast and exact algorithm for computing the Earth Mover's
Distance (EMD) between a pair of histograms. The efficiency of the new algorithm enables …

For analyzing shapes of planar, closed curves, we propose differential geometric
representations of curves using their direction functions and curvature functions. Shapes are …

This paper proposes a novel graph matching algorithm and applies it to shape recognition
based on object silhouettes. The main idea is to match skeleton graphs by comparing the …