Features Of Individual Objects Research Articles

An International and Multidisciplinary Consensus on the Labeling of Spatial Neglect Using a Modified Delphi Method

Survivors of neurologic injury (most commonly stroke or traumatic brain injury) frequently experience a disorder in which contralesionally positioned objects or the contralesional features of individual objects are often left unattended or underappreciated. The disorder is known by >200 unique labels in the literature, which potentially causes confusion for patients and their families, complicates literature searches for researchers and clinicians, and promotes a fractionated conceptualization of the disorder. The objective of this Delphi was to determine if consensus (≥75% agreement) could be reached by an international and multidisciplinary panel of researchers and clinicians with expertise on the topic.To accomplish this aim, we used a modified Delphi method in which 66 researchers and/or clinicians with expertise on the topic completed at least 1 of 4 iterative rounds of surveys. Per the Delphi method, panelists were provided with results from each round prior to responding to the survey in the subsequent round with the explicit intention of achieving consensus. The panel ultimately reached consensus that the disorder should be consistently labeled spatial neglect. Based on the consensus reached by our expert panel, we recommend that researchers and clinicians use the label spatial neglect when describing the disorder in general and more specific labels pertaining to subtypes of the disorder when appropriate.

When time shifts the boundaries: Isolating the role of forgetting in children’s changing category representations

In studies of children’s categorization, researchers have typically studied how encoding characteristics of exemplars contribute to children’s generalization. However, it is unclear whether children’s internal cognitive processes alone, independent of new information, may also influence their generalization. Thus, we examined the role that one cognitive process, forgetting, plays in shaping children’s category representations by conducting three experiments. In the first two experiments, participants (NExp1 = 37, Mage = 4.02 years; NExp2 = 32, Mage = 4.48 years) saw a novel object labeled by the experimenter and then saw five new objects with between one and five features changed from the learned exemplar. The experimenter asked whether each object was a member of the same category as the exemplar; children saw the five new objects either immediately or after a 5-minute delay. Children endorsed category membership at higher rates at immediate test than at delayed test, suggesting that children’s category representations became narrower over time. In Experiment 3, we investigated forgetting as a key mechanism underlying the narrowing found in Experiments 1 and 2. We showed participants (NExp3 = 34, Mage = 4.20 years) the same exemplars used in Experiments 1 and 2; then, either immediately or after a 5-minute delay, we showed children seven individual object features and asked if each one had been part of the exemplar. Children’s accuracy was lower after the delay, showing that they did indeed forget individual features. Taken together, these results show that forgetting plays an important role in changing children’s newly-learned categories over time.

Segmentation Clustering Algorithm for Point Cloud Processing of Targets on The Ground

After the ground extraction algorithm, there are multiple objects, including the target in the non-ground point cloud. To effectively extract the features of individual objects and overcome the dependence of the traditional algorithm based on the normal vector and curvature of the region growing point cloud segmentation method on the initial point, the normal vector angle in the neighborhood, and the curvature threshold selection. In this paper, we propose a fast clustering segmentation method for region-growing point clouds based on neighborhood density. The test results show that the point cloud segmentation algorithm proposed in this paper has better performance than the traditional Euclidean clustering point cloud segmentation algorithm and region growing point cloud segmentation algorithm in terms of timeliness and correct segmentation rate. This new segmentation clustering algorithm can quickly implement automatic point cloud clustering segmentation of ground objects.

Sentiment Interaction Distillation Network for Image Sentiment Analysis

Sentiment is a high-level abstraction, and it is a challenging task to accurately extract sentimental features from visual contents due to the “affective gap”. Previous works focus on extracting more concrete sentimental features of individual objects by introducing saliency detection or instance segmentation into their models, neglecting the interaction among objects. Inspired by the observation that interaction among objects can impact the sentiment of images, we propose the Sentiment Interaction Distillation (SID) Network, which utilizes object sentimental interaction to guide feature learning. Specifically, we first utilize a panoptic segmentation method to obtain objects in images; then, we propose a sentiment-related edge generation method and employ Graph Convolution Network to aggregate and propagate object relation representation. In addition, we propose a knowledge distillation framework to utilize interaction information guiding global context feature learning, which can avoid noisy features introduced by error propagation and a varying number of objects. Experimental results show that our method outperforms the state-of-the-art algorithm, e.g., about 1.2% improvement on the Flickr dataset and 1.7% on the most challenging subset of Twitter I. It is demonstrated that the reasonable use of interaction features can improve the performance of sentiment analysis.

Mice recognize 3D objects from recalled 2D pictures, support for picture-object equivalence

Picture-object equivalence or recognizing a three-dimensional (3D) object after viewing a two-dimensional (2D) photograph of that object, is a higher-order form of visual cognition that may be beyond the perceptual ability of rodents. Behavioral and neurobiological mechanisms supporting picture-object equivalence are not well understood. We used a modified visual recognition memory task, reminiscent of those used for primates, to test whether picture-object equivalence extends to mice. Mice explored photographs of an object during a sample session, and 24 h later were presented with the actual 3D object from the photograph and a novel 3D object, or the stimuli were once again presented in 2D form. Mice preferentially explored the novel stimulus, indicating recognition of the “familiar” stimulus, regardless of whether the sample photographs depicted radially symmetric or asymmetric, similar, rotated, or abstract objects. Discrimination did not appear to be guided by individual object features or low-level visual stimuli. Inhibition of CA1 neuronal activity in dorsal hippocampus impaired discrimination, reflecting impaired memory of the 2D sample object. Collectively, results from a series of experiments provide strong evidence that picture-object equivalence extends to mice and is hippocampus-dependent, offering important support for the appropriateness of mice for investigating mechanisms of human cognition.

Differentiation of the Legal Regulation of the Pledge Depending on from the Object

The article raises the question of differentiating the legal regulation of legal relations arising from a pledge, depending on the object of the pledge. Of course, the pledge as a way of securing the fulfillment of obligations is characterized by common features and general approaches to regulation, regardless of the object, at the same time, the features of individual objects require the specification of the relevant rules. The ongoing debate in science regarding the ratio of objects of civil rights, as well as the lack of unity on the issue of the ratio of individual objects, gives rise to a discussion regarding certain types of collateral, classified depending on the object. The author pays special attention to the pledge of property rights and proposes an approach on the relationship between certain types of property rights, in particular, rights of obligation, rights of participants in legal entities and exclusive rights to the results of intellectual activity.

Improving text-to-image generation with object layout guidance

The automatic generation of realistic images directly from a story text is a very challenging problem, as it cannot be addressed using a single image generation approach due mainly to the semantic complexity of the story text constituents. In this work, we propose a new approach that decomposes the task of story visualization into three phases: semantic text understanding, object layout prediction, and image generation and refinement. We start by simplifying the text using a scene graph triple notation that encodes semantic relationships between the story objects. We then introduce an object layout module to capture the features of these objects from the corresponding scene graph. Specifically, the object layout module aggregates individual object features from the scene graph as well as averaged or likelihood object features generated by a graph convolutional neural network. All these features are concatenated to form semantic triples that are then provided to the image generation framework. For the image generation phase, we adopt a scene graph image generation framework as stage-I, which is refined using a StackGAN as stage-II conditioned on the object layout module and the generated output image from stage-I. Our approach renders object details in high-resolution images while keeping the image structure consistent with the input text. To evaluate the performance of our approach, we use the COCO dataset and compare it with three baseline approaches, namely, sg2im, StackGAN and AttnGAN, in terms of image quality and user evaluation. According to the obtained assessment results, our object layout guidance-based approach significantly outperforms the abovementioned baseline approaches in terms of the accuracy of semantic matching and realism of the generated images representing the story text sentences.

Mirrored conditional random field model for object recognition in indoor environments

Traditional object recognition algorithms are based on a commonly adopted closed-set hypothesis, assuming that the knowledge given in training is complete. However, real situations are often open and nonstatic, in which case the models only obtain incomplete knowledge during the training phase. This paper proposes a new type of conditional random field (CRF) model to solve a special case of incomplete knowledge, in which the visual appearance of certain objects changes significantly between training and testing, and as a result, certain unary features (features of individual objects) extracted from red green blue-depth (RGB-D) images are no longer reliable. Mirror nodes are introduced into the architecture based on the standard CRF model to build the mirrored conditional random field (Mirror-CRF) model, which integrates two types of object nodes: original nodes and mirror nodes. The mirror nodes have no unary features, only pairwise features, which describe relationships between two objects and are more reliable than unary features for object recognition in the case of appearance variation. The experimental results show that the Mirror-CRF model reduces the influence of significant changes in the appearance of certain objects and improves the object recognition ability under the condition of incomplete knowledge.

Approximation of real data by fuzzy sets for the classification problem

The article deals with the method of classification of real data using the apparatus of fuzzy sets and fuzzy logic as a flexible tool for learning and recognition of natural objects on the example of oil and gas prospecting sections of the Dnieper-Donetsk basin. The real data in this approach are the values for the membership function that are obtained not through subjective expert judgment but from objective measurements. It is suggested to approximate the fuzzy set membership functions by using training data to use the approximation results obtained during the learning phase at the stage of identifying unknown objects. In the first step of learning, each traditional future of a learning data is matched by a primary traditional one-dimensional set whose membership function can only take values from a binary set — 0 if the learning object does not belong to the set, and 1 if the learning object belongs to the set. In the second step, the primary set is mapped to a fuzzy set, and the parameters of the membership function of this fuzzy set are determined by approximating this function of the traditional set membership. In the third step, the set of one-dimensional fuzzy sets that correspond to a single feature of the object is mapped to a fuzzy set that corresponds to all the features of the object in the training data set. Such a set is the intersection of fuzzy sets of individual features, to which the blurring and concentration operations of fuzzy set theory are applied in the last step. Thus, the function of belonging to a fuzzy set of a class is the operation of choosing a minimum value from the functions of fuzzy sets of individual features of objects, which are reduced to a certain degree corresponding to the operation of blurring or concentration. The task of assigning the object under study to a particular class is to compare the values of the membership functions of a multidimensional fuzzy set and to select the class in which the membership function takes the highest value. Additionally, after the training stage, it is possible to determine the degree of significance of an object future, which is an indistinctness index, to remove non-essential data (object futures) from the analysis.

Concurrent Cortical Representations of Function- and Size-Related Object Affordances: An fMRI Study

Previous work has shown that the perception of a graspable object may automatically potentiate actions that are tailored to specific action-related features of the object (e.g., its size) and may be related to its immediate grasping as well as to its long-term, functional use. We investigated the neural correlates of function- and size-related object affordances that may be concurrently potentiated by a graspable object. Participants were lying in a MR scanner holding a large switch in one hand and a small switch in the other hand. They passively attended a large or a small object with clearly separated functional and graspable end that was displayed centrally at an average angle of 45 degrees. Participants responded to the direction of an arrow that was overlaid on the object after a mean period of 1,000 ms after object onset and was pointing to the left or to the right with equal probability. Response times were shorter when the arrow pointed to the functional end of the object and when the responses were made with the switch that was congruent to the size of the perceived object. A clear distinction was found in the representation of function- and size-related affordances; the former was represented in the posterior parietal cortex and the latter in prefrontal, premotor, and primary sensorimotor cortices. We conclude that different aspects of object-directed actions may be automatically potentiated by individual object features and are represented in distinct brain areas.

Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images

Urban functional zones, such as commercial, residential, and industrial zones, are basic units of urban planning, and play an important role in monitoring urbanization. However, historical functional-zone maps are rarely available for cities in developing countries, as traditional urban investigations focus on geographic objects rather than functional zones. Recent studies have sought to extract functional zones automatically from very-high-resolution (VHR) satellite images, and they mainly concentrate on classification techniques, but ignore zone segmentation which delineates functional-zone boundaries and is fundamental to functional-zone analysis. To resolve the issue, this study presents a novel segmentation method, geoscene segmentation, which can identify functional zones at multiple scales by aggregating diverse urban objects considering their features and spatial patterns. In experiments, we applied this method to three Chinese cities—Beijing, Putian, and Zhuhai—and generated detailed functional-zone maps with diverse functional categories. These experimental results indicate our method effectively delineates urban functional zones with VHR imagery; different categories of functional zones extracted by using different scale parameters; and spatial patterns that are more important than the features of individual objects in extracting functional zones. Accordingly, the presented multiscale geoscene segmentation method is important for urban-functional-zone analysis, and can provide valuable data for city planners.

Oculomotion mediates attentional guidance toward temporarily close objects

ABSTRACTPrevious research has identified multiple features of individual objects that are capable of guiding visual attention. However, in dynamic multi-element displays not only individual object features but also changing spatial relations between two or more objects might signal relevance. Here we report a series of experiments that investigated the hypothesis that reduced inter-object spacing guides visual attention toward the corresponding objects. Our participants discriminated between different probes that appeared on moving objects while we manipulated spatial proximity between the objects at the moment of probe onset. Indeed, our results confirm that there is a bias toward temporarily close objects, which persists even when such a bias is harmful for the actual task (Experiments 1a and 1b). Remarkably, this bias is mediated by oculomotor processes. Controlling for eye-movements reverses the pattern of results (Experiment 2a), whereas the location of the gaze tends toward the temporarily close objects under free viewing conditions (Experiment 2b). Taken together, our results provide insights into the interplay of attentional and oculomotor processes during dynamic scene processing. Thereby, they also add to the growing body of evidence showing that within dynamic perception, attentional and oculomotor processes act conjointly and are hardly separable.

Materiality, Labor, and Signification of Sacred Objects in Japanese Buddhism

Recent studies on Buddhist materiality tend to focus on specific objects and their ritual uses, without dedicating much attention to processes of production of those objects and their actual makers. This article begins to redress this situation by outlining a general theoretical framework for the study of Buddhist objects and material culture in general through their continuous transformations—a framework that takes into account not only the ontological status and phenomenological features of individual objects, but also their signification and the various types of labor involved in their production and fruition. After proposing a general typology of objects, in order to gain a better sense of the ontological extension of Buddhism, the article also discusses the types of labor and practical activities involved in the production and use of Buddhist objects. Next, it deals with different aspects that determine the value of Buddhist sacred objects, and addresses modes of transformation affecting Buddhist objects through time and space, envisioned here as instances of broader processes of semiotic transformation (semiomorphosis). While this paper mostly examines objects within the Japanese Buddhist tradition, it hopes to offer a contribution to the study of practical materiality and labor in other Buddhist traditions as well.

Modulation of taxonomic (versus thematic) similarity judgments and product choices by inducing local and global processing

ABSTRACTPerceived similarity is influenced by both taxonomic and thematic relations. Assessing taxonomic relations requires comparing individual features of objects whereas assessing thematic relations requires exploring how objects functionally interact. These processes appear to relate to different thinking styles: abstract thinking and a global focus may be required to explore functional interactions whereas attention to detail and a local focus may be required to compare specific features. In four experiments we explored this idea by assessing whether a preference for taxonomic or thematic relations could be created by inducing a local or global perceptual processing style. Experiments 1–3 primed processing style via a perceptual task and used a choice task to examine preference for taxonomic (versus thematic) relations. Experiment 4 induced processing style and examined the effect on similarity ratings for pairs of taxonomic and thematically related items. In all cases processing style influenced preference for taxonomic/thematic relations.

Real-time classification of humans versus animals using profiling sensors and hidden Markov tree model

Linear pyroelectric array sensors have enabled useful classifications of objects such as humans and animals to be performed with relatively low-cost hardware in border and perimeter security applications. Ongoing research has sought to improve the performance of these sensors through signal processing algorithms. In the research presented here, we introduce the use of hidden Markov tree (HMT) models for object recognition in images generated by linear pyroelectric sensors. HMTs are trained to statistically model the wavelet features of individual objects through an expectation–maximization learning process. Human versus animal classification for a test object is made by evaluating its wavelet features against the trained HMTs using the maximum-likelihood criterion. The classification performance of this approach is compared to two other techniques; a texture, shape, and spectral component features (TSSF) based classifier and a speeded-up robust feature (SURF) classifier. The evaluation indicates that among the three techniques, the wavelet-based HMT model works well, is robust, and has improved classification performance compared to a SURF-based algorithm in equivalent computation time. When compared to the TSSF-based classifier, the HMT model has a slightly degraded performance but almost an order of magnitude improvement in computation time enabling real-time implementation.

From perceptual to language-mediated categorization.

From at least two months onwards, infants can form perceptual categories. During the first year of life, object knowledge develops from the ability to represent individual object features to representing correlations between attributes and to integrate information from different sources. At the end of the first year, these representations are shaped by labels, opening the way to conceptual knowledge. Here, we review the development of object knowledge and object categorization over the first year of life. We then present an artificial neural network model that models the transition from early perceptual categorization to categories mediated by labels. The model informs a current debate on the role of labels in object categorization by suggesting that although labels do not act as object features they nevertheless affect perceived similarity of perceptually distinct objects sharing the same label. The model presents the first step of an integrated account from early perceptual categorization to language-based concept learning.

Age-related decline of precision and binding in visual working memory.

Working memory declines with normal aging, but the nature of this impairment is debated. Studies based on detecting changes to arrays of visual objects have identified two possible components to age-related decline: a reduction in the number of items that can be stored, or a deficit in maintaining the associations (bindings) between individual object features. However, some investigations have reported intact binding with aging, and specific deficits arising only in Alzheimer’s disease. Here, using a recently developed continuous measure of recall fidelity, we tested the precision with which adults of different ages could reproduce from memory the orientation and color of a probed array item. The results reveal a further component of cognitive decline: an age-related decrease in the resolution with which visual information can be maintained in working memory. This increase in recall variability with age was strongest under conditions of greater memory load. Moreover, analysis of the distribution of errors revealed that older participants were more likely to incorrectly report one of the unprobed items in memory, consistent with an age-related increase in misbinding. These results indicate a systematic decline with age in working memory resources that can be recruited to store visual information. The paradigm presented here provides a sensitive index of both memory resolution and feature binding, with the potential for assessing their modulation by interventions. The findings have implications for understanding the mechanisms underpinning working memory deficits in both health and disease.

Perceptual averaging by eye and ear: Computing summary statistics from multimodal stimuli

Beyond perceiving the features of individual objects, we also have the intriguing ability to efficiently perceive average values of collections of objects across various dimensions. Over what features can perceptual averaging occur? Work to date has been limited to visual properties, but perceptual experience is intrinsically multimodal. In an initial exploration of how this process operates in multimodal environments, we explored statistical summarizing in audition (averaging pitch from a sequence of tones) and vision (averaging size from a sequence of discs), and their interaction. We observed two primary results. First, not only was auditory averaging robust, but if anything, it was more accurate than visual averaging in the present study. Second, when uncorrelated visual and auditory information were simultaneously present, observers showed little cost for averaging in either modality when they did not know until the end of each trial which average they had to report. These results illustrate that perceptual averaging can span different sensory modalities, and they also illustrate how vision and audition can both cooperate and compete for resources.

Dissociation between Awareness and Spatial Coding: Evidence from Unilateral Neglect

Prevalent theories about consciousness propose a causal relation between lack of spatial coding and absence of conscious experience: The failure to code the position of an object is assumed to prevent this object from entering consciousness. This is consistent with influential theories of unilateral neglect following brain damage, according to which spatial coding of neglected stimuli is defective, and this would keep their processing at the nonconscious level. Contrary to this view, we report evidence showing that spatial coding and consciousness can dissociate. A patient with left neglect, who was not aware of contralesional stimuli, was able to process their color and position. However, in contrast to (ipsilesional) consciously perceived stimuli, color and position of neglected stimuli were processed separately. We propose that individual object features, including position, can be processed without attention and consciousness and that conscious perception of an object depends on the binding of its features into an integrated percept.

Feature Processing and Illusory Conjunctions in Infants' Long-Term Memory

Theories of visual information processing and feature integration, along with previous infant research, have indicated that only individual object features, and not the feature relations, are perceptually processed by early visual mechanisms. Previous research from within the memory domain has further suggested that, based on the encoding of features, errors in memory in the form of illusory conjunctions (i.e. miscombination of features from disparate objects) are likely. Considering that research has shown that infants' memory is particularly reliant on features, their recognition mechanisms should be quite susceptible to memory conjunction errors. Using the mobile-conjugate reinforcement paradigm, young infants were trained with mobiles displaying both O's and R's (or P's and Q's) and tested with stimuli that contained a miscombination of those features such as a Q (or an R), or a stimulus that did not contain these features (S). Results revealed that infants miscombined the individual features of the O and R (and P and Q) such that they recognized a Q (and R). Infants discriminated, however, the S mobile. These findings support previous research and the notion that object features encoded in infant long-term memory are likely stored as independent units irrespective of the spatial relations among those features, consequently allowing for the miscombination of features upon retrieval. Interestingly, however, infants discriminated a mobile displaying the same features as in the R but in a different spatial combination, suggesting that infants encoded some spatial characteristic of the individual feature. In sum, the present findings suggest that individual object features, and not the spatial feature relations, have a preferential status in young infants' long-term memory.