Color diagnosticity in object recognition

Does color influence object recognition? In the present study, the degree to which an object was associated with a specific color was referred to ascolor diagnosticity. Using a feature listing and typicality measure, objects were identified as either high in color diagnosticity or low in color diagnosticity. According to the color diagnosticity hypothesis, color should more strongly influence the recognition of high color diagnostic (HCD) objects (e.g., a banana) than the recognition of low color diagnostic (LCD) objects (e.g., a lamp). This prediction was supported by results from classification, naming, and verification experiments, in which subjects were faster to identify color versions of HCD objects than they were to identify achromatic versions and incongruent color versions. In contrast, subjects were no faster to identify color versions of LCD objects than they were to identify achromatic and incongruent color versions. Moreover, when shape information was degraded but color information preserved, subjects were less impaired in their recognition of degraded HCD objects than of degraded LCD objects, relative to their nondegraded versions. Collectively, these results suggest that color plays a role in the recognition of HCD objects.     

The role of color diagnosticity in object recognition and representation

The role of color diagnosticity in object recognition and representation was assessed in three Experiments. In Experiment 1a, participants named pictured objects that were strongly associated with a particular color (e.g., pumpkin and orange). Stimuli were presented in a congruent color, incongruent color, or grayscale. Results indicated that congruent color facilitated naming time, incongruent color impeded naming time, and naming times for grayscale items were situated between the congruent and incongruent conditions. Experiment 1b replicated Experiment 1a using a verification task. Experiment 2 employed a picture rebus paradigm in which participants read sentences one word at a time that included pictures of color diagnostic objects (i.e., pictures were substituted for critical nouns). Results indicated that the “reading” times of these pictures mirrored the pattern found in Experiment 1. In Experiment 3, an attempt was made to override color diagnosticity using linguistic context (e.g., a pumpkin was described as painted green). Linguistic context did not override color diagnosticity. Collectively, the results demonstrate that color information is regularly utilized in object recognition and representation for highly color diagnostic items.     

Coordinate transformations in object recognition

A basic problem of visual perception is how human beings recognize objects after spatial transformations. Three central classes of findings have to be accounted for: (a) Recognition performance varies systematically with orientation, size, and position; (b) recognition latencies are sequentially additive, suggesting analogue transformation processes; and (c) orientation and size congruency effects indicate that recognition involves the adjustment of a reference frame. All 3 classes of findings can be explained by a transformational framework of recognition: Recognition is achieved by an analogue transformation of a perceptual coordinate system that aligns memory and input representations. Coordinate transformations can be implemented neurocomputationally by gain (amplitude) modulation and may be regarded as a general processing principle of the visual cortex.     

Untangling invariant object recognition

Despite tremendous variation in the appearance of visual objects, primates can recognize a multitude of objects, each in a fraction of a second, with no apparent effort. However, the brain mechanisms that enable this fundamental ability are not understood. Drawing on ideas from neurophysiology and computation, we present a graphical perspective on the key computational challenges of object recognition, and argue that the format of neuronal population representation and a property that we term 'object tangling' are central. We use this perspective to show that the primate ventral visual processing stream achieves a particularly effective solution in which single-neuron invariance is not the goal. Finally, we speculate on the key neuronal mechanisms that could enable this solution, which, if understood, would have far-reaching implications for cognitive neuroscience.     

Bio-inspired computational object classification model for object recognition

Human beings can effortlessly perceive stimuli through their sensory systems to learn, understand, recognize and act on our environment or context. Over the years, efforts have been made to enable cybernetic entities to be close to performing human perception tasks; and in general, to bring artificial intelligence closer to human intelligence.Neuroscience and other cognitive sciences provide evidence and explanations of the functioning of certain aspects of visual perception in the human brain. Visual perception is a complex process, and its has been divided into several parts. Object classification is one of those parts; it is necessary for carrying out the declarative interpretation of the environment. This article deals with the object classification problem.In this article, we propose a computational model of visual classification of objects based on neuroscience, it consists of two modular systems: a visual processing system, in charge of the extraction of characteristics; and a perception sub-system, which performs the classification of objects based on the features extracted by the visual processing system.With the results obtained, a set of aspects are analyzed using similarity and dissimilarity matrices. Also based on the neuroscientific evidence and the results obtained from this research, some aspects are suggested for consideration to improve the work in the future and bring us closer to performing the task of visual classification as humans do.     

The role of object recognition in young infants' object segregation

Needham's (2001, this issue) new results confirm that young infants draw on experientially derived representations in resolving individuation ambiguities due to shared boundaries between adjacent objects. They extend previous findings in a surprising way: The memory representations that infants draw upon have bound together information about shape, color, and pattern. Our commentary on these important results draws a distinction between two senses of "recognition" and asks in which sense object recognition contributes to object individuation in these experiments.     

The role of the human medial temporal lobe in object recognition and object discrimination.

This paper reviews evidence from neuropsychological patient studies relevant to two questions concerning the functions of the medial temporal lobe in humans. The first is whether the hippocampus and the adjacent perirhinal cortex make different contributions to memory. Data are discussed from two patients with adult-onset bilateral hippocampal damage who show a sparing of item recognition relative to recall and certain types of associative recognition. It is argued that these data are consistent with Aggleton and Brown's (1999) proposal that familiarity-based recognition memory is not dependent on the hippocampus but is mediated by the perirhinal cortex and dorso-medial thalamic nucleus. The second question is whether the recognition memory deficit observed in medial temporal lobe amnesia can be explained by a deficit in perceptual processing and representation of objects rather than a deficit in memory per se. The finding that amnesics were impaired at recognizing, after short delays, patterns that they could successfully discriminate suggests that their memory impairment did not result from an object-processing deficit. The possibility remains, however, that the human perirhinal cortex plays a role in object processing, as well as in recognition memory, and data are presented that support this possibility.     

Influencesicture context on object recognition

The effect of sorrounding context on the recognition of objects from briefly presented pictures was investigated. Forty-eight undergraduates saw 100 msec displays of either line drawings containing several objects embedded in context or drawings of object arrays without background context. Following each exposure they were required to select from among four objects the one that had been contained in the picture. Presentation of objects in context aided recognition only when incorrect response alternatives were inconsistent with the picture context. The results suggest that context contributes to the construction of a general characterization of the pictures which provides expectancies regarding the identity of specific objects.     

One-trial object recognition by rats

Four experiments examined the ability of rats to solve problems analogous to those used with primates, where they were required to remember an object seen on a single trial. In the first experiment, rats were rewarded for selecting the novel of two goal boxes in a Y-maze (nonmatching). Different pairs of goal boxes were used for every trial within a session in order to increase the salience of the positive stimulus and to exclude the use of odour trails. The animals rapidly learnt this one-trial object recognition task and performed well above chance after retention intervals as long as 120 sec. A control experiment confirmed that the rats could not use spatial cues to solve the task. A third experiment showed that rats could also learn to select the familiar of two boxes in a one-trial test of object matching. In the final experiment the rats were unable to acquire a win-stay/lose-shift strategy when tested in a comparable manner.     

Three-dimensional features facilitate object recognition

Abstract

A priming paradigm was used to investigate the contribution of local features and global shape information in object recognition. Five types of incomplete forms were used as primes: (1) forms with both maxima (local curvature) and midsegments of edges present and aligned on the outline contour; (2) forms similar in global shape to the first version of stimuli, but with misaligned elements; (3) forms with only maxima; (4) forms with only midsegments of edges; and (5) forms containing 3D comer junctions (in Experiments 3 and 4). The target was an outline drawing of an object from which the incomplete prime was derived. Subjects were asked to name the target as rapidly as possible. Primes were presented at levels of contrast corresponding to identification thresholds, as well as above and below threshold levels (determined in Experiments 1 and 3). Facilitation effects relative to a neutral (no prime) condition occurred at threshold and above threshold for primes with aligned elements, forms with only maxima, and forms with only midsegments. Priming occurred only above threshold for forms with non-aligned elements. In Experiment 4 the presence of 3D local features increased the magnitude of priming relative to forms with midsegments and to forms with flat corners (in Experiment 2). This result suggests that 3D features facilitate object identification either because objects are stored in the form of volumetric entities or because 3D features are extracted early in visual processing.     

Effects of active navigation on object recognition in virtual environments.

We investigated the importance and efficiency of active and passive exploration on the recognition of objects in a variety of virtual environments (VEs). In this study, 54 participants were randomly allocated into one of active and passive navigation conditions. Active navigation was performed by allowing participants to self-pace and control their own navigation, but passive navigation was conducted by forced navigation. After navigating VEs, participants were asked to recognize the objects that had been in the VEs. Active navigation condition had a significantly higher percentage of hit responses (t (52) = 4.000, p < 0.01), and a significantly lower percentage of miss responses (t (52) = -3.763, p < 0.01) in object recognition than the passive condition. These results suggest that active navigation plays an important role in spatial cognition as well as providing an explanation for the efficiency of learning in a 3D-based program.     

Sleep deprivation impairs object recognition in mice

Many studies in animals and humans suggest that sleep facilitates learning, memory consolidation, and retrieval. Moreover, sleep deprivation (SD) incurred after learning, impaired memory in humans, mice, rats, and hamsters. We investigated the importance of sleep and its timing in an object recognition task in OF1 mice subjected to 6h SD either immediately after the acquisition phase (0-6 SD) or 6h later (7-12 SD), and in corresponding undisturbed controls. Motor activity was continuously recorded with infrared sensors. All groups explored two familiar, previously encountered objects to a similar extent, both at the end of the acquisition phase and 24h later during the test phase, indicating intact familiarity detection. During the test phase 0-6 SD mice failed to discriminate between the single novel and the two familiar objects. In contrast, the 7-12 SD group and the two control groups explored the novel object significantly longer than the two familiar objects. Plasma corticosterone levels determined after SD did not differ from time-matched undisturbed controls, but were significantly below the level measured after learning alone. ACTH did not differ between the groups. Therefore, it is unlikely that stress contributed to the memory impairment. We conclude that the loss of sleep and the activities the mice engaged in during the SD, impaired recognition memory retrieval, when they occurred immediately after acquisition. The delayed SD enabled memory consolidation during the 6h when the mice were allowed to sleep, and had no detrimental effect on memory. Neither SD schedule impaired object familiarity processing, suggesting that only specific cognitive abilities were sensitive to the intervention. Sleep may either actively promote memory formation, or alternatively, sleep may provide optimal conditions of non-interference for consolidation.     

Attention to distinguishing features in object recognition

This study advances the hypothesis that, in the course of object recognition, attention is directed to distinguishing features: visual information that is diagnostic of object identity in a specific context. In five experiments, observers performed an object categorization task involving drawings of fish (Experiments 1–4) and photographs of natural sea animals (Experiment 5). Allocation of attention to distinguishing and non-distinguishing features was examined using primed-matching (Experiment 1) and visual probe (Experiments 2, 4, 5) methods, and manipulated by spatial precuing (Experiment 3). Converging results indicated that in performing the object categorization task, attention was allocated to the distinguishing features in a context-dependent manner, and that such allocation facilitated performance. Based on the view that object recognition, like categorization, is essentially a process of discrimination between probable alternatives, the implications of the findings for the role of attention to distinguishing features in object recognition are discussed.     

The role of context in object recognition

In the real world, objects never occur in isolation; they co-vary with other objects and particular environments, providing a rich source of contextual associations to be exploited by the visual system. A natural way of representing the context of an object is in terms of its relationship to other objects. Alternately, recent work has shown that a statistical summary of the scene provides a complementary and effective source of information for contextual inference, which enables humans to quickly guide their attention and eyes to regions of interest in natural scenes. A better understanding of how humans build such scene representations, and of the mechanisms of contextual analysis, will lead to a new generation of computer vision systems.     

Indirect object recognition: evidence for associative processes in recognition memory

Rats' exploration of stimulus P (e.g., a domestic object) is reduced following either its direct exposure or its indirect exposure and is taken to indicate recognition memory. Procedures for demonstrating indirect object recognition involve an initial presentation of object P with stimulus X (and of an object Q with stimulus Y). On test, stimulus X is presented with objects P and Q and rats' exploration of Q exceeds their exploration of P. One interpretation here is that the presentation of stimulus X on test associatively activates the memory of object P, which diminishes exploration of P relative to Q. It is possible, instead, that performance is simply the result of a novel pattern of stimulation generated by the unfamiliar combination of X and Q. The authors modified this procedure to reduce the likelihood of such a process. Their procedure involved first the presentation of PX and QY before the presentation of stimulus X alone. During the test that followed, objects P and Q were presented but stimulus X was removed. The authors found that exploration of Q remained greater than that of P despite these modifications and discuss some theoretical implications of indirect, associative processes in recognition memory.     

The diagnosticity of individual data for model selection: Comparing signal-detection models of recognition memory

We tested whether the unequal-variance signal-detection (UVSD) and dual-process signal-detection (DPSD) models of recognition memory mimic the behavior of each other when applied to individual data. Replicating previous results, there was no mimicry for an analysis that fit each individual, summed the goodness-of-fit values over individuals, and compared the two sums (i.e., a single model selection). However, when the models were compared separately for each individual (i.e., multiple model selections), mimicry was substantial. To quantify the diagnosticity of the individual data, we used mimicry to calculate the probability of making a model selection error for each individual. For nondiagnostic data (high model selection error), the results were compatible with equal-variance signal-detection theory. Although neither model was justified in this situation, a forced-choice between the UVSD and DPSD models favored the DPSD model for being less flexible. For diagnostic data (low model selection error), the UVSD model was selected more often.