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      A Review of Human Activity Recognition Methods

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      Frontiers in Robotics and AI
      Frontiers Media SA

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          A tutorial on support vector regression

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            Canonical correlation analysis: an overview with application to learning methods.

            We present a general method using kernel canonical correlation analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation and enables a comparison between the text and images. In the experiments, we look at two approaches of retrieving images based on only their content from a text query. We compare orthogonalization approaches against a standard cross-representation retrieval technique known as the generalized vector space model.
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              A survey of affect recognition methods: audio, visual, and spontaneous expressions.

              Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions despite the fact that deliberate behaviour differs in visual appearance, audio profile, and timing from spontaneously occurring behaviour. To address this problem, efforts to develop algorithms that can process naturally occurring human affective behaviour have recently emerged. Moreover, an increasing number of efforts are reported toward multimodal fusion for human affect analysis including audiovisual fusion, linguistic and paralinguistic fusion, and multi-cue visual fusion based on facial expressions, head movements, and body gestures. This paper introduces and surveys these recent advances. We first discuss human emotion perception from a psychological perspective. Next we examine available approaches to solving the problem of machine understanding of human affective behavior, and discuss important issues like the collection and availability of training and test data. We finally outline some of the scientific and engineering challenges to advancing human affect sensing technology.
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                Author and article information

                Journal
                Frontiers in Robotics and AI
                Front. Robot. AI
                Frontiers Media SA
                2296-9144
                November 16 2015
                November 16 2015
                : 2
                :
                Article
                10.3389/frobt.2015.00028
                9b117aa9-72ae-44cd-8bed-dd15af3f4397
                © 2015

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