Exploratory topic modeling with distributional semantics

As we continue to collect and store textual data in a multitude of domains, we are regularly confronted with material whose largely unknown thematic structure we want to uncover. With unsupervised, exploratory analysis, no prior knowledge about the content is required and highly open-ended tasks can be supported. In the past few years, probabilistic topic modeling has emerged as a popular approach to this problem. Nevertheless, the representation of the latent topics as aggregations of semi-coherent terms limits their interpretability and level of detail. This paper presents an alternative approach to topic modeling that maps topics as a network for exploration, based on distributional semantics using learned word vectors. From the granular level of terms and their semantic similarity relations global topic structures emerge as clustered regions and gradients of concepts. Moreover, the paper discusses the visual interactive representation of the topic map, which plays an important role in supporting its exploration.Comment: Conference: The Fourteenth International Symposium on Intelligent Data Analysis (IDA 2015

Visual search for featural singletons: No top-down modulation, only bottom-up priming.

The present study investigated the effect of top-down knowledge on search for a feature singleton (a "pop-out target"). In a singleton detection task, advance cueing of the dimension of upcoming singleton resulted in cueing costs and benefits (Experiment 1). When the search for the singleton stayed the same but only the response requirements were changed, advance cueing failed to have an effect (Experiments 2 and 3). In singleton search only bottom-up priming plays a role (Experiments 4 and 5). We conclude that expectancy-based, top-down knowledge cannot guide the search for a featural singleton. Bottom-up priming that does facilitate search for a featural singleton cannot be influenced by top-down control. The study demonstrates that effects often attributed to early top-down guidance may represent effects that occur later in processing or represent bottom-up priming effects. © 2006 Psychology Press Ltd

Deployment of spatial attention towards locations in memory representations: an EEG study

Recalling information from visual short-term memory (VSTM) involves the same neural mechanisms as attending to an actually perceived scene. In particular, retrieval from VSTM has been associated with orienting of visual attention towards a location within a spatially-organized memory representation. However, an open question concerns whether spatial attention is also recruited during VSTM retrieval even when performing the task does not require access to spatial coordinates of items in the memorized scene. The present study combined a visual search task with a modified, delayed central probe protocol, together with EEG analysis, to answer this question. We found a temporal contralateral negativity (TCN) elicited by a centrally presented go-signal which was spatially uninformative and featurally unrelated to the search target and informed participants only about a response key that they had to press to indicate a prepared target-present vs. -absent decision. This lateralization during VSTM retrieval (TCN) provides strong evidence of a shift of attention towards the target location in the memory representation, which occurred despite the fact that the present task required no spatial (or featural) information from the search to be encoded, maintained, and retrieved to produce the correct response and that the go-signal did not itself specify any information relating to the location and defining feature of the target

Contextual cropping and scaling of TV productions

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-011-0804-3. Copyright @ Springer Science+Business Media, LLC 2011.In this paper, an application is presented which automatically adapts SDTV (Standard Definition Television) sports productions to smaller displays through intelligent cropping and scaling. It crops regions of interest of sports productions based on a smart combination of production metadata and systematic video analysis methods. This approach allows a context-based composition of cropped images. It provides a differentiation between the original SD version of the production and the processed one adapted to the requirements for mobile TV. The system has been comprehensively evaluated by comparing the outcome of the proposed method with manually and statically cropped versions, as well as with non-cropped versions. Envisaged is the integration of the tool in post-production and live workflows

Negative emotional stimuli reduce contextual cueing but not response times in inefficient search

In visual search, previous work has shown that negative stimuli narrow the focus of attention and speed reaction times (RTs). This paper investigates these two effects by first asking whether negative emotional stimuli narrow the focus of attention to reduce the learning of a display context in a contextual cueing task and, second, whether exposure to negative stimuli also reduces RTs in inefficient search tasks. In Experiment 1, participants viewed either negative or neutral images (faces or scenes) prior to a contextual cueing task. In a typical contextual cueing experiment, RTs are reduced if displays are repeated across the experiment compared with novel displays that are not repeated. The results showed that a smaller contextual cueing effect was obtained after participants viewed negative stimuli than when they viewed neutral stimuli. However, in contrast to previous work, overall search RTs were not faster after viewing negative stimuli (Experiments 2 to 4). The findings are discussed in terms of the impact of emotional content on visual processing and the ability to use scene context to help facilitate search

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201

Attentional Performance, Age and Scholastic Achievement in Healthy Children

Attentional processes in children play a critical role in daily school demands and accomplishments. Studies on the association of attentional processes with school achievement and age in healthy school children are scarce. The aim of the present study was to identify correlations between dimensions of attentional performance, scholastic achievement and age.An extensive testing battery was used to assess a wide range of attentional dimensions. A principal component analysis revealed three factors that are related to attentional performance (distractibility, lapses of attention, cognitive speed). Age was negatively associated with distractibility, lapses of attention and cognitive speed, indicating that distractibility and lapses of attention decreased with age in healthy children and resulted in lower cognitive speed.Attentional processes in healthy children should be measured in relation to distractibility, lapses of attention and cognitive speed