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Saliency detection has been a hot topic in recent years. Its popularity is mainly because of its theoretical meaning for explaining human attention and applicable aims in segmentation, recognition, etc. Nevertheless, traditional algorithms are mostly based on unsupervised techniques, which have limited learning ability. The obtained saliency map is also inconsistent with many properties of human behavior...
Human movement analysis is a long-studied, but still important and challenging research area in visual surveillance. It involves many fundamental problems in computer vision such as human detection, segmentation and tracking, and higher level problems such as human gesture, action and event recognition. Shape is the most dominant cue for detecting humans due to large appearance variability. In this...
Activity recognition has been applied to many varied applications ranging from surveillance to medical analysis. Interpreting human actions is often a complex problem for computer vision. Actions can be classified through shape, motion or region based algorithms. While all have their distinct advantages, we consider a feature extraction approach using convexity defects. This algorithmic approach offers...
In this paper, we investigate the task of human action detection in crowded videos. Different from action analysis in clean scenes, action detection in crowded environments is difficult due to the cluttered backgrounds, high densities of people and partial occlusions. This paper proposes a method for action detection based on masks. No human segmentation or tracking technique is required. To cope...
The objective of the current work is to develop an automatic tool to identify microbiological data types using computer vision and pattern recognition. Current systems rely on the subjective reading of profiles by a human expert. This process is time-consuming and prone to errors. Bacteriophage (phage) typing & Fluorescent imaging methods are used to extract representative feature profiles and...
The analysis of foot movements is important in sports and computer vision can be used to provide feedback to athletes about their foot placements. This paper describes a method for locating and rendering an athlete's foot placements over a geometric plane for professional analysis. Results and method for our implementation are discussed. This method uses background subtraction and blob segmentation...
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