SPiKeS: Superpixel-Keypoints structure for robust visual tracking

Robust Visual Tracking with Dual Group Structure

The “sparse representation”-based tracking framework generally considers the testing candidates and dictionary atoms individually, thus failing to model the structured information within data. In this paper, we present a robust tracking framework by exploiting the dual group structure of both candidate samples and dictionary templates, and formulate the sparse representation at group level. The...

Learning Object Intrinsic Structure for Robust Visual Tracking

In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a low dimensional manifold and can be learned from training data. Based on this assumption, firstly we derived the dimensionality reduction and density estimation algorithm for unsupervised learning of object intrinsic ...

Visual Tracking by Local Superpixel Matching with Markov Random Field

Robust Object Tracking Using Constellation Model with Superpixel

Tracking objects under occlusion or non-rigid deformation poses a major problem: appearance variation of target makes existing bounding rectangle based representation vulnerable to background noise imported during adaptive appearance update. We address the object tracking problem by exploring superpixel based visual information around the target. Instead of representing each object with a singl...

Robust Visual Person Tracking for Interactive Displays

We present an approach to real-time person tracking in crowded and/or unknown environments using integration of multiple visual modalities. We combine stereo, color, and face detection modules into a single robust system, and show an initial application in an interactive, faceresponsive display. Dense, real-time stereo processing is used to isolate users from other objects and people in the bac...