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The nature of human behavior makes Bayesian methods particularly well-suited for its automated analysis. It is complex, highly variable, frequently inconsistent and is often the consequence of thought processes that we know not of. Advanced modeling techniques that specifically take uncertainty into account are therefore highly desirable. If it were not for the associated computational cost, whether...
This chapter introduces the sequence analysis problem in machine learning. The problem is formulated in terms of two major issues: The first is the classification (assignment of a label to an entire sequence of observations), and the second is the labeling (assignment of a label to each observation in a sequence). The chapter applies the framework of probabilistic graphical models to introduce two...
Detection and tracking of action content in the field of view of a camera is a significant step that needs to be completed prior to analysis. The detection task can be performed by either examining a single image or by analyzing the motion in a series of consecutive frames from a video. The tracking task, in contrast, requires multiple images and can be performed by association of detected objects...
Visual attention is one of the key mechanisms of perception that enables humans to efficiently select the visual data of most potential interest. Machines face similar challenges as humans: they have to deal with a large amount of input data and have to select the most promising parts. In this chapter, we explain the underlying biological and psychophysical grounding of visual attention, show how...
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