We present a hand-and-foot-based multimodal interaction approach for handheld devices.
Our method combines input modalities (ie, hand and foot) and provides a coordinated output …

In this paper, we present a comprehensive survey of Markov Random Fields (MRFs) in
computer vision and image understanding, with respect to the modeling, the inference and …

There is an increasing interest in creating pervasive games based on emerging interaction
technologies. In order to develop touch-less, interactive and augmented reality games on …

摘要形状匹配及分类是计算机视觉中的重要问题. 近年来, 以形状上下文为代表的基于轮廓的
形状匹配方法和以奇点图为代表的基于骨架的形状匹配方法获得了长足的发展 …

Deployment of modern data-driven machine learning methods, most often realized by deep
neural networks (DNNs), in safety-critical applications such as health care, industrial plant …

Markov random field (MRF) is a widely used probabilistic model for expressing interaction of
different events. One of the most successful applications is to solve image labeling problems …

This paper analyzes the problems of document image recognition and the existing solutions.
Document recognition algorithms have been studied for quite a long time, but despite this …

Abstract Dynamic Time Warping (DTW) is probably the most popular distance measure for
time series data, because it captures flexible similarities under time distortions. However …

This paper describes a novel model for time series recognition called a Dynamic Time
Warping Neural Network (DTW-NN). DTW-NN is a feedforward neural network that exploits …

This paper presents a new efficient method for crop row detection which uses a dynamic
programming technique to combine image evidence and prior knowledge about the …