Examples of gesture control are based on the exposure fusion algorithm [3] , and roll, pitch and yaw were considered as candidate movements for adjusting the 3 parameters associated with the exposure fusion algorithm.
Sample text:```The present observations support and extend earlier contentions that Parkinson patients prefer to adopt a closedloop control mode, adjusting their movements continuously on the basis of available visual information (Flowers 1976).```
Sample intent: result
Sample text:```For example, Kawato et al. (1990) suggested that movement trajectories can be projected using critical via-points through which the trajectory has to pass at a certain time, rather than in terms of the moment-by-moment dynamics of the implemented movement trajectory. Optimal trajectories can then be learnt by applying local optimising principles for getting from one via-point to the next. In this way, impoverished predictions can be used to monitor rich implementations. In the same way, language users might predict particularly crucial aspects of an utterance, but the aspects that they predict will depend on the circumstances. More generally, Meyer & Hagoort question the value of predicting one’s own utterance. They argue that prediction is useful when it is likely to differ from the actual event. This is the case when predicting another person’s behaviour or when the result of one’s action is uncertain (e.g., moving in a strong wind). But they argue that people are confident about their own speech. Meyer & Hagoort admit that they will tend to be less confident in dialogue, and we agree. But more important, we argue that the behaviour of the production implementer is not fully determined by the production command, because the complex processes involved in production are subject to internal (“neural”) noise or priming (i.e., influences that may not be a result of the production command). Assuming that these sources of noise do not necessarily affect forward modelling as well, predicted speech may differ from actual speech. In addition, prediction is useful even if the behaviour is fully predictable, because it allows the actor to plan future behaviour on the basis of the prediction. In fact, we made such a proposal in relation to the order of heavy and light phrases (see sect. 3.1, target article). Hartsuiker claims that our account incorrectly predicts an early competitor effect in Huettig and Hartsuiker (2010). His claim is based on the assumption that Response/Pickering & Garrod: An integrated theory of language production and comprehension```
Sample intent: method



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:```The next communication [2] considered the most general characteristics of the parameter of spa tial EEG synchronization (the average in each of the fre quency bands of the EEG’s coherence value), such as multiplicity, directedness, and reproducibility of varia tions of this parameter owing to the change of state of the subjects.```
Sample intent: method



Sample text:```Our results further confirm previous findings on the differential regulatory mechanisms for Hoxa3 and Hoxb3 expression in r5 and r6 by kreisler (Manzanares et al., 1997, 1999a,b, 2001).```
Sample intent: result



Sample text:```…with several action-based models of selective action that suggest turning one’s visual attention to an object or location in space may be the same process as preparing a movement to that object/location (e.g., Rizzolatti et al.1994; Tipper et al.1992; Welsh and Elliott 2004b; Welsh et al.1999).```
Sample intent: background
Sample text:```The present observations support and extend earlier contentions that Parkinson patients prefer to adopt a closedloop control mode, adjusting their movements continuously on the basis of available visual information (Flowers 1976).```
Sample intent: result



Sample text:```…with several action-based models of selective action that suggest turning one’s visual attention to an object or location in space may be the same process as preparing a movement to that object/location (e.g., Rizzolatti et al.1994; Tipper et al.1992; Welsh and Elliott 2004b; Welsh et al.1999).```
Sample intent: background



Sample text:```The next communication [2] considered the most general characteristics of the parameter of spa tial EEG synchronization (the average in each of the fre quency bands of the EEG’s coherence value), such as multiplicity, directedness, and reproducibility of varia tions of this parameter owing to the change of state of the subjects.```
Sample intent: method



Sample text:```Our results further confirm previous findings on the differential regulatory mechanisms for Hoxa3 and Hoxb3 expression in r5 and r6 by kreisler (Manzanares et al., 1997, 1999a,b, 2001).```
Sample intent: result



Sample text:```These are in keeping with earlier studies on the steadystate response (2, 5, 8), step-function response, (3, 5, 6, 14) and sinusoidal response ( 14) of the various vascular beds.```
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:```Following the experimental design proposed in Yannakakis and Hallam (2007c) and Yannakakis et al. (2008) for effectively capturing the level of entertainment, the test-bed game under investigation is played in variants.```
Sample intent: background



Sample text:```For example, Kawato et al. (1990) suggested that movement trajectories can be projected using critical via-points through which the trajectory has to pass at a certain time, rather than in terms of the moment-by-moment dynamics of the implemented movement trajectory. Optimal trajectories can then be learnt by applying local optimising principles for getting from one via-point to the next. In this way, impoverished predictions can be used to monitor rich implementations. In the same way, language users might predict particularly crucial aspects of an utterance, but the aspects that they predict will depend on the circumstances. More generally, Meyer & Hagoort question the value of predicting one’s own utterance. They argue that prediction is useful when it is likely to differ from the actual event. This is the case when predicting another person’s behaviour or when the result of one’s action is uncertain (e.g., moving in a strong wind). But they argue that people are confident about their own speech. Meyer & Hagoort admit that they will tend to be less confident in dialogue, and we agree. But more important, we argue that the behaviour of the production implementer is not fully determined by the production command, because the complex processes involved in production are subject to internal (“neural”) noise or priming (i.e., influences that may not be a result of the production command). Assuming that these sources of noise do not necessarily affect forward modelling as well, predicted speech may differ from actual speech. In addition, prediction is useful even if the behaviour is fully predictable, because it allows the actor to plan future behaviour on the basis of the prediction. In fact, we made such a proposal in relation to the order of heavy and light phrases (see sect. 3.1, target article). Hartsuiker claims that our account incorrectly predicts an early competitor effect in Huettig and Hartsuiker (2010). His claim is based on the assumption that Response/Pickering & Garrod: An integrated theory of language production and comprehension```
Sample intent: method



Sample text:```Pupillometry has been proposed as a simple and sensitive tool to detect subclinical autonomic dysfunction [30,31].```
Sample intent: background



Sample text:```…methods rely on some additional and often heuristic step to generate an initial solution, such as adversarially-trained neural networks [Conneau et al., 2018, Zhang et al., 2017a,b], robust self-learning [Artetxe et al., 2018b] or
5This can be easily verified by noting that the…```
Sample intent: background