Searching for semantic person queries using channel representations

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to relate and easy to understand. However such queries are not easily utilised within intelligent surveillance systems as they are difficult to transform into a representation that can be searched for automatically in large camera networks. In this paper we propose a novel approach that transforms such a semantic query into an avatar that is searchable within a video stream, and demonstrate state-of-the-art performance for locating a subject in video based on a description.

On the symbiosis of law and truth in Christian theology: Reconciling universal and particular through the Pauline law of love

This article argues that the secular liberal and positivist foundations of the modern Western legal system render it violent. In particular, the liberal exclusion of faith and subjectivity in favour of abstract and universal reason in conjunction with its privileging of individual autonomy at the expense of the community leads to alienation of the individual from the community. Similarly, the positivist exclusion of faith and theology from law, with its enforced conformity to the posited law, also results in this violence of alienation. In response, this article proposes a new foundation for law, a natural law based in the truth of Trinitarian theology articulated by John Milbank. In the Trinity, the members exist as a perfect unity in diversity, providing a model for the reconciliation of the legal individual and community: the law of love. Through the law of love as the basic norm, individuals love their neighbours as themselves, reconciling the particular and the universal, and providing a community of peace rather than violence.

Medical semantic similarity with a neural language model

Advances in neural network language models have demonstrated that these models can effectively learn representations of words meaning. In this paper, we explore a variation of neural language models that can learn on concepts taken from structured ontologies and extracted from free-text, rather than directly from terms in free-text. This model is employed for the task of measuring semantic similarity between medical concepts, a task that is central to a number of techniques in medical informatics and information retrieval. The model is built with two medical corpora (journal abstracts and patient records) and empirically validated on two ground-truth datasets of human-judged concept pairs assessed by medical professionals. Empirically, our approach correlates closely with expert human assessors ($\approx$ 0.9) and outperforms a number of state-of-the-art benchmarks for medical semantic similarity. The demonstrated superiority of this model for providing an effective semantic similarity measure is promising in that this may translate into effectiveness gains for techniques in medical information retrieval and medical informatics (e.g., query expansion and literature-based discovery).

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Exploiting inference from semantic annotations for information retrieval

The increasing amount of information that is annotated against standardised semantic resources offers opportunities to incorporate sophisticated levels of reasoning, or inference, into the retrieval process. In this position paper, we reflect on the need to incorporate semantic inference into retrieval (in particular for medical information retrieval) as well as previous attempts that have been made so far with mixed success. Medical information retrieval is a fertile ground for testing inference mechanisms to augment retrieval. The medical domain offers a plethora of carefully curated, structured, semantic resources, along with well established entity extraction and linking tools, and search topics that intuitively require a number of different inferential processes (e.g., conceptual similarity, conceptual implication, etc.). We argue that integrating semantic inference in information retrieval has the potential to uncover a large amount of information that otherwise would be inaccessible; but inference is also risky and, if not used cautiously, can harm retrieval.

Searching for people using semantic soft biometric descriptions

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to communicate and easy to understand. However such queries are not easily utilised within intelligent video surveillance systems, as they are difficult to transform into a representation that can be utilised by computer vision algorithms. In this paper we propose a novel approach that transforms such a semantic query into an avatar in the form of a channel representation that is searchable within a video stream. We show how spatial, colour and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter like approach. We demonstrate state-of-the-art performance for locating a subject in video based on a description, achieving a relative performance improvement of 46.7% over the baseline. We also apply this approach to person re-detection, and show that the approach can be used to re-detect a person in a video steam without the use of person detection.

Neural correlates of semantic priming for ambiguous words: An event-related fMRI study

We investigated the neural correlates of semantic priming by using event-related fMRI to record blood oxygen level dependent (BOLD) responses while participants performed speeded lexical decisions (word/nonword) on visually presented related versus unrelated prime-target pairs. A long stimulus onset asynchrony of 1000 ms was employed, which allowed for increased controlled processing and selective frequency-based ambiguity priming. Conditions included an ambiguous word prime (e.g. bank) and a target related to its dominant (e.g. money) or subordinate meaning (e.g. river). Compared to an unrelated condition, primed dominant targets were associated with increased activity in the LIFG, the right anterior cingulate and superior temporal gyrus, suggesting postlexical semantic integrative mechanisms, while increased right supramarginal activity for the unrelated condition was consistent with expectancy based priming. Subordinate targets were not primed and were associated with reduced activity primarily in occipitotemporal regions associated with word recognition, which may be consistent with frequency-based meaning suppression. These findings provide new insights into the neural substrates of semantic priming and the functional-anatomic correlates of lexical ambiguity suppression mechanisms.

Dopaminergic neuromodulation of semantic processing: A 4-T fMRI study with levodopa

There is emerging evidence that alterations in dopaminergic transmission can influence semantic processing, yet the neural mechanisms involved are unknown. The influence of levodopa (L-DOPA) on semantic priming was investigated in healthy individuals (n=20) using event-related functional magnetic resonance imaging with a randomized, double-blind crossover design. Critical prime-target pairs consisted of a lexical ambiguity prime and 1) a target related to the dominant meaning of the prime (e.g., bank-money), 2) a target related to the subordinate meaning (e.g., fence-sword), or 3) an unrelated target (e.g., ball-desk). Behavioral data showed that both dominant and subordinate meanings were primed on placebo. In contrast, there was preserved priming of dominant meanings and no significant priming of subordinate meanings on L-DOPA, the latter associated with decreased anterior cingulate and dorsal prefrontal cortex activity. Dominant meaning activation on L-DOPA was associated with increased activity in the left rolandic operculum and left middle temporal gyrus. These findings suggest that L-DOPA enhances frequency-based semantic focus via prefrontal and temporal modulation of automatic semantic priming and through engagement of anterior cingulate mechanisms supporting attentional/controlled priming.

Classic identity negative priming involves accessing semantic representations in the left anterior temporal cortex

Classic identity negative priming (NP) refers to the finding that when an object is ignored, subsequent naming responses to it are slower than when it has not been previously ignored (Tipper, S.P., 1985. The negative priming effect: inhibitory priming by ignored objects. Q. J. Exp. Psychol. 37A, 571-590). It is unclear whether this phenomenon arises due to the involvement of abstract semantic representations that the ignored object accesses automatically. Contemporary connectionist models propose a key role for the anterior temporal cortex in the representation of abstract semantic knowledge (e.g., McClelland, J.L., Rogers, T.T., 2003. The parallel distributed processing approach to semantic cognition. Nat. Rev. Neurosci. 4, 310-322), suggesting that this region should be involved during performance of the classic identity NP task if it involves semantic access. Using high-field (4 T) event-related functional magnetic resonance imaging, we observed increased BOLD responses in the left anterolateral temporal cortex including the temporal pole that was directly related to the magnitude of each individual's NP effect, supporting a semantic locus. Additional signal increases were observed in the supplementary eye fields (SEF) and left inferior parietal lobule (IPL).

Perfusion fMRI evidence for priming of shared feature-to-lexical connections during cumulative semantic interference in spoken word production

The speed at which target pictures are named increases monotonically as a function of prior retrieval of other exemplars of the same semantic category and is unaffected by the number of intervening items. This cumulative semantic interference effect is generally attributed to three mechanisms: shared feature activation, priming and lexical-level selection. However, at least two additional mechanisms have been proposed: (1) a 'booster' to amplify lexical-level activation and (2) retrieval-induced forgetting (RIF). In a perfusion functional Magnetic Resonance Imaging (fMRI) experiment, we tested hypotheses concerning the involvement of all five mechanisms. Our results demonstrate that the cumulative interference effect is associated with perfusion signal changes in the left perirhinal and middle temporal cortices that increase monotonically according to the ordinal position of exemplars being named. The left inferior frontal gyrus (LIFG) also showed significant perfusion signal changes across ordinal presentations; however, these responses did not conform to a monotonically increasing function. None of the cerebral regions linked with RIF in prior neuroimaging and modelling studies showed significant effects. This might be due to methodological differences between the RIF paradigm and continuous naming as the latter does not involve practicing particular information. We interpret the results as indicating priming of shared features and lexical-level selection mechanisms contribute to the cumulative interference effect, while adding noise to a booster mechanism could account for the pattern of responses observed in the LIFG.

The structure and connectivity of semantic memory in the healthy older adult brain

The anterior temporal lobes (ATLs) have been proposed to serve as a "hub" linking amodal or domain general information about the meaning of words, objects, facts and people distributed throughout the brain in semantic memory. The two primary sources of evidence supporting this proposal, viz. structural imaging studies in semantic dementia (SD) patients and functional imaging investigations, are not without problems. Similarly, knowledge about the anatomo-functional connectivity of semantic memory is limited to a handful of intra-operative electrocortical stimulation (IES) investigations in patients. Here, using principal components analyses (PCA) of a battery of conceptual and non-conceptual tests coupled with voxel based morphometry (VBM) and diffusion tensor imaging (DTI) in a sample of healthy older adults aged 55-85. years, we show that amodal semantic memory relies on a predominantly left lateralised network of grey matter regions involving the ATL, posterior temporal and posterior inferior parietal lobes, with prominent involvement of the left inferior fronto-occipital fasciculus (IFOF) and uncinate fasciculus fibre pathways. These results demonstrate relationships between semantic memory, brain structure and connectivity essential for human communication and cognition.

The semantic interference effect in the picture-word paradigm: An event-related fMRI study employing overt responses

We used event-related functional magnetic resonance imaging (fMRI) to investigate neural responses associated with the semantic interference (SI) effect in the picture-word task. Independent stage models of word production assume that the locus of the SI effect is at the conceptual processing level (Levelt et al. [1999]: Behav Brain Sci 22:1-75), whereas interactive models postulate that it occurs at phonological retrieval (Starreveld and La Heij [1996]: J Exp Psychol Learn Mem Cogn 22:896-918). In both types of model resolution of the SI effect occurs as a result of competitive, spreading activation without the involvement of inhibitory links. These assumptions were tested by randomly presenting participants with trials from semantically-related and lexical control distractor conditions and acquiring image volumes coincident with the estimated peak hemodynamic response for each trial. Overt vocalization of picture names occurred in the absence of scanner noise, allowing reaction time (RT) data to be collected. Analysis of the RT data confirmed the SI effect. Regions showing differential hemodynamic responses during the SI effect included the left mid section of the middle temporal gyrus, left posterior superior temporal gyrus, left anterior cingulate cortex, and bilateral orbitomedial prefrontal cortex. Additional responses were observed in the frontal eye fields, left inferior parietal lobule, and right anterior temporal and occipital cortex. The results are interpreted as indirectly supporting interactive models that allow spreading activation between both conceptual processing and phonological retrieval levels of word production. In addition, the data confirm that selective attention/response suppression has a role in resolving the SI effect similar to the way in which Stroop interference is resolved. We conclude that neuroimaging studies can provide information about the neuroanatomical organization of the lexical system that may prove useful for constraining theoretical models of word production.