Cost-Effective HITs for Relative Similarity Comparisons

Similarity comparisons of the form "Is object a more similar to b than to c?" are useful for computer vision and machine learning applications. Unfortunately, an embedding of $n$ points is specified by $n^3$ triplets, making collecting every triplet an expensive task. In noticing this difficulty, other researchers have investigated more intelligent triplet sampling techniques, but they do not study their effectiveness or their potential drawbacks. Although it is important to reduce the number of collected triplets, it is also important to understand how best to display a triplet collection task to a user. In this work we explore an alternative display for collecting triplets and analyze the monetary cost and speed of the display. We propose best practices for creating cost effective human intelligence tasks for collecting triplets. We show that rather than changing the sampling algorithm, simple changes to the crowdsourcing UI can lead to much higher quality embeddings. We also provide a dataset as well as the labels collected from crowd workers.Comment: 7 pages, 7 figure

Normalized cuts in 3-d for spinal mri segmentation

Abstract—Segmentation of medical images has become an indispensable process to perform quantitative analysis of images of human organs and their functions. Normalized Cuts is a spectral graph theoretic method that readily admits combinations of different features for image segmentation. The computational demand imposed by Normalized Cuts has been successfully alleviated with the Nyström approximation method for applications different than medical imaging. In this paper we discuss the application of Normalized Cuts with the Nyström approximation method to segment vertebral bodies from sagittal T1-weighted magnetic resonance images of the spine. The magnetic resonance images were pre-processed by the anisotropic diffusion algorithm, and 3D local histograms of brightness was chosen as the segmentation feature. Results of the segmentation as well as limitations and challenges in this area are presented. Index Terms — Magnetic resonance imaging (MRI), Normalized Cuts (NCut), Nyström approximation method, segmentation, spine

Periodic motion detection and segmentation via approximate sequence alignment

A method for detecting and segmenting periodic motion is presented. We exploit periodicity as a cue and detect periodic motion in complex scenes where common methods for motion segmentation are likely to fail. We note that periodic motion detection can be seen as an approximate case of sequence alignment where an image sequence is matched to itself over one or more periods of time. To use this observation, we first consider alignment of two video sequences obtained by independently moving cameras. Under assumption of constant translation, the fundamental matrices and the homographies are shown to be time-linear matrix functions. These dynamic quantities can be estimated by matching corresponding space-time points with similar local motion and shape. For periodic motion, we match corresponding points across periods and develop a RANSAC procedure to simultaneously estimate the period and the dynamic geometric transformations between periodic views. Using this method, we demonstrate detection and segmentation of human periodic motion in complex scenes with non-rigid backgrounds, moving camera and motion parallax. 1

SPATIO-TEMPORAL TEXTURE SYNTHESIS AND IMAGE INPAINTING FOR VIDEO APPLICATIONS

In this paper we investigate the application of texture synthesis and image inpainting techniques for video applications. Working in the non-parametric framework, we use 3D patches for matching and copying. This ensures temporal continuity to some extent which is not possible to obtain by working with individual frames. Since, in present application, patches might contain arbitrary shaped and multiple disconnected holes, fast fourier transform (FFT) and summed area table based sum of squared difference (SSD) calculation [1] cannot be used. We propose a modification of above scheme which allows its use in present application. This results in significant gain of efficiency since search space is typically huge for video applications. 1