Attention please: evaluative priming effects in a valent/non-valent categorization task (Reply to Werner and Rothermund, 2013)

It has previously been argued (a) that automatic evaluative stimulus processing is dependent upon feature-specific attention allocation (FSAA) and (b) that evaluative priming effects can arise in the absence of dimensional overlap between the prime set and the response set. In opposition to these claims, Werner and Rothermund (2013) recently reported that they were unable to replicate the evaluative priming effect in a valent/non-valent categorisation task. In this manuscript, I report the results of a conceptual replication of the studies by Werner and Rothermund (2013). A clear-cut evaluative priming effect was found, thus supporting the initial claims about FSAA and dimensional overlap. An explanation for these divergent findings is discussed

Real-time, long-term hand tracking with unsupervised initialization

This paper proposes a complete tracking system that is capable of long-term, real-time hand tracking with unsupervised initialization and error recovery. Initialization is steered by a three-stage hand detector, combining spatial and temporal information. Hand hypotheses are generated by a random forest detector in the first stage, whereas a simple linear classifier eliminates false positive detections. Resulting detections are tracked by particle filters that gather temporal statistics in order to make a final decision. The detector is scale and rotation invariant, and can detect hands in any pose in unconstrained environments. The resulting discriminative confidence map is combined with a generative particle filter based observation model to enable robust, long-term hand tracking in real-time. The proposed solution is evaluated using several challenging, publicly available datasets, and is shown to clearly outperform other state of the art object tracking methods

Sparse optical flow regularisation for real-time visual tracking

Optical flow can greatly improve the robustness of visual tracking algorithms. While dense optical flow algorithms have various applications, they can not be used for real-time solutions without resorting to GPU calculations. Furthermore, most optical flow algorithms fail in challenging lighting environments due to the violation of the brightness constraint. We propose a simple but effective iterative regularisation scheme for real-time, sparse optical flow algorithms, that is shown to be robust to sudden illumination changes and can handle large displacements. The algorithm proves to outperform well known techniques in real life video sequences, while being much faster to calculate. Our solution increases the robustness of a real-time particle filter based tracking application, consuming only a fraction of the available CPU power. Furthermore, a new and realistic optical flow dataset with annotated ground truth is created and made freely available for research purposes

Gesture based human-computer interface for 3D design

modeling are amongst the most important fields of interest in current computer vision research. However, traditional hand recognition systems can only operate in constrained environments using coloured gloves or static backgrounds and do not allow for 3D object manipulation. The goal of this research is to develop real-time camera based solutions to control 3D modeling applications using natural hand gestures

3D Face tracking and gaze estimation using a monocular camera

Estimating a user’s gaze direction, one of the main novel user interaction technologies, will eventually be used for numerous applications where current methods are becoming less effective. In this paper, a new method is presented for estimating the gaze direction using Canonical Correlation Analysis (CCA), which finds a linear relationship between two datasets defining the face pose and the corresponding facial appearance changes. Afterwards, iris tracking is performed by blob detection using a 4-connected component labeling algorithm. Finally, a gaze vector is calculated based on gathered eye properties. Results obtained from datasets and real-time input confirm the robustness of this metho

Evaluative priming in the pronunciation task a preregistered replication and extension

We replicated and extended a study by Spruyt and Hermans (2008) in which picture primes engendered an evaluative-priming effect on the pronunciation of target words. As preliminary steps, we assessed data reproducibility of the original study, conducted Pilot Study I to identify highly semantically related prime-target pairs, reanalyzed the original data excluding such pairs, conducted Pilot Study II to demonstrate that we can replicate traditional associative priming effects in the pronunciation task, and conducted Pilot Study III to generate relatively unrelated sets of prime pictures and target words. The main study comprised three between-participants conditions: (1) a close replication of the original study, (2) the same condition excluding highly related prime-target pairs, and (3) a condition based on the relatively unrelated sets of prime pictures and target words developed in Pilot Study III. There was little evidence for an evaluative priming effect independent of semantic relatedness

Effects in the affect misattribution procedure are modulated by feature-specific attention allocation

We examined whether automatic stimulus evaluation as measured by the Affect Misattribution Procedure (AMP) is moderated by the degree to which attention is assigned to the evaluative stimulus dimension (i.e., feature-specific attention allocation, FSAA). In two experiments, one group of participants completed a standard AMP while attending to evaluative stimulus information. A second group of participants completed the AMP while attending to non-evaluative stimulus information. In line with earlier work, larger AMP effects were observed when participants were encouraged to attend to evaluative stimulus information than when they were not. These observations support the idea that the impact of FSAA on measures of automatic stimulus evaluation results from a genuine change in the degree of automatic stimulus evaluation rather than a change in the degree to which automatic stimulus evaluation is picked up by these measures

On the (un)conditionality of automatic attitude activation: the valence proportion effect

Affective priming studies have shown that participants are faster to pronounce affectively polarized target words that are preceded by affectively congruent prime words than affectively polarized target words that are preceded by affectively incongruent prime words. We examined whether affective priming of naming responses depends on the valence proportion (i.e., the proportion of stimuli that are affectively polarized). In one group of participants, experimental trials were embedded in a context of filler trials that consisted of affectively polarized stimulus materials (i.e., high valence proportion condition). In a second group, the same set of experimental trials was embedded in a context of filler trials consisting of neutral stimuli (i.e., low valence proportion condition). Results showed that affective priming of naming responses was significantly stronger in the high valence proportion condition than in the low valence proportion condition. We conclude that (a) subtle aspects of the procedure can influence affective priming of naming responses, (b) finding affective priming of naming responses does not allow for the conclusion that affective stimulus processing is unconditional, and (c) affective stimulus processing depends on selective attention for affective stimulus information

Body dissatisfaction revisited : on the importance of implicit beliefs about actual and ideal body image

Body dissatisfaction (i.e., a negative attitude towards one’s own physical appearance) is assumed to originate from a perceived discrepancy between the actual physical appearance (i.e., actual body image) and the desired ideal state of the body (i.e., ideal body image). We assessed implicit beliefs about these two aspects of the body image independently using two Relational Responding Tasks (RRT) in a sample of participants who were either low or high in explicitly reported body dissatisfaction. As hypothesized, differences in body dissatisfaction exerted a differential influence on the two RRT scores. The implicit belief that one is thin was less pronounced in participants who were strongly dissatisfied with their body relative to participants who were more satisfied with their body. The implicit desire to be thin (i.e., thin ideal body image), in contrast, tended to be more pronounced in participants who exhibited a high degree of body dissatisfaction as compared to participants who exhibited a low degree of body dissatisfaction. Hierarchical regression analyses also revealed that the RRT scores were predictive of self-reported body dissatisfaction, even over and above the predictive validity of some (but not all) explicit predictors of body dissatisfaction that were included in the present study. More generally, these findings contribute to the empirical validation of the RRT as a measure of implicit beliefs in the context of body dissatisfaction