How are second-order (texture-defined) and third-order (pattern-tracking) motions processed in our brains? As shown here in the context of an ambiguous motion task involving a nominal second-order stimuli first devised by Werkhoven et al., [Werkhoven, P., Sperling, G. & Chubb, C. (1993) Vision Res. 33, 463-485.], the observers fell into two distinct groups based on the direction of perceived mo...

Linear Blur Motion is one of the most common degradation functions that corrupt images. Since 1976 many researchers have tried to estimate blur motion parameters and this problem can be solved for noise free images but in the case of noisy images this can be done when the image SNR is low. In this paper, we consider pattern recognition with ensemble neural networks for the case of fingerprints;...

This paper introduces a method for human action recognition based on optical flow motion features extraction. Automatic spatial and temporal alignments are combined together in order to encourage the temporal consistence on each action by an enhanced dynamic time warping (DTW) algorithm. At the same time, a fast method based on coarse-to-fine DTW constraint to improve computational performance ...

Motion features based on optical flow are very powerful in tasks such as the recognition of human actions or gestures. Usually, they are combined with gradient information to form a set of spatiotemporal features. However, humans can recognize gestures and actions and thus derive the implied motion out of static images alone. We model this associative recognition within a learned hierarchy of n...

Continuous hand gesture recognition requires the detection of gestures in a video stream and their classification. In this paper two continuous recognition solutions using HiddenMarkov-Models (HMMs) are compared. The first approach uses a motion detection algorithm to isolate gesture candidates followed by a HMM recognition step. The second approach is a single-stage, HMM-based spotting method ...