In the experiments, two popular benchmarks are used to evaluate the proposed method: the CohnKanade [25] and MMI [] facial expression databases.
Sample text:```As a novel biomechanical analysis from video recordings, a Model-Based Image-Matching (MBIM) motion analysis technique has been introduced to investigate human motion from uncalibrated video sequences (Krosshaug and Bahr, 2005).```
Sample intent: background
Sample text:```Our results confi rm previous studies that reached the same conclusion (Boushey et al 1994; Vermeulen et al 2000; Till et al 2005; Marcucci et al 2005).```
Sample intent: result



Sample text:```As a novel biomechanical analysis from video recordings, a Model-Based Image-Matching (MBIM) motion analysis technique has been introduced to investigate human motion from uncalibrated video sequences (Krosshaug and Bahr, 2005).```
Sample intent: background



Sample text:```Similarly, in a study on 60 subjects, blinks were measured at the beginning and end of a working day (Caffier et al., 2003). Although no significant difference between alert and drowsy phases was found, a slightly decreased blink rate during drowsy phase was reported. However, these results contradict the findings of Morris and Miller (1996) about the efficiency of F in a moving base-flight simulator with 10 sleep-deprived pilots.```
Sample intent: result



Sample text:```The tests were as follows: the C-MMSE [13], the LMT [18], the RCFT [19], the Boston Naming Test (the 30-item version) [20,21], the Animal Verbal Fluency Test [22], the Symbol Digit Modalities Test [23], the Trail Making Test‚Äì```
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Sample text:```have been proposed as potential alternatives to the Turing Test, specifically targeting its potential weaknesses and inadequacy [1].```
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Sample text:```Following past work, we show that such basis models can be learned from 2D annotations using techniques adapted from nonrigid structure from motion (SFM) [20, 19].```
Sample intent: method



Sample text:```have been proposed as potential alternatives to the Turing Test, specifically targeting its potential weaknesses and inadequacy [1].```
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Sample text:```Note that in their pioneering paper Calvet and Fisher (2002) proposed the simplified version of the construction of Mannersalo et al (2002).```
Sample intent: method



Sample text:```In this study, we generalized previous results regarding the quasi-Gaussian shape and the scalar property using the SBF model [13,21,52].```
Sample intent: result



Sample text:```While this method is known to be generally reliable, there are some questions about the representativeness of the data used [25].```
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Sample text:```Over the last few years, many different local interest point detectors (like Harris3D [16], Cuboid [6], Hessian [35] or Dense sampling [33]) and many spatio-temporal descriptors (like HOG [17], HOG3D [14], HOF [17], Cuboid [6] or ESURF [35]) have been proposed.```
Sample intent: method



Sample text:```The items are internally consistent and reproducible and the questionnaire may therefore be considered to have at least as favourable levels of reliability as clinical scores used to assess outcomes (Koran 1975).```
Sample intent: result



Sample text:```Our results confi rm previous studies that reached the same conclusion (Boushey et al 1994; Vermeulen et al 2000; Till et al 2005; Marcucci et al 2005).```
Sample intent: result



Sample text:```In this study, we used the Knowledge Map Concept Indexer (KMCI) (Denny et al., 2009), a general-purpose NLP engine, to process all paper titles from American Journal of Epidemiology (AJE).```
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Sample text:```We assessed participants’ dehumanization of Arabs by using
the Ascent scale of blatant dehumanization (Kteily et al., 2015).```
Sample intent: method