scholarly journals Infant Visual Attention and Stimulus Repetition Effects on Object Recognition

2017 ◽  
Vol 90 (4) ◽  
pp. 1027-1042 ◽  
Author(s):  
Greg D. Reynolds ◽  
John E. Richards
Author(s):  
Debi Prosad Dogra

Scene understanding and object recognition heavily depend on the success of visual attention guided salient region detection in images and videos. Therefore, summarizing computer vision techniques that take the help of visual attention models to accomplish video object recognition and tracking, can be helpful to the researchers of computer vision community. In this chapter, it is aimed to present a philosophical overview of the possible applications of visual attention models in the context of object recognition and tracking. At the beginning of this chapter, a brief introduction to various visual saliency models suitable for object recognition is presented, that is followed by discussions on possible applications of attention models on video object tracking. The chapter also provides a commentary on the existing techniques available on this domain and discusses some of their possible extensions. It is believed that, prospective readers will benefit since the chapter comprehensively guides a reader to understand the pros and cons of this particular topic.


1981 ◽  
Vol 33 (3) ◽  
pp. 241-265 ◽  
Author(s):  
Lester E. Krueger ◽  
Ronald G. Shapiro

Specific intertrial effects (repetition effects) and general intertrial effects (refractoriness or persisting attention to the preceding trial) were studied with the same-different judgment task, which dissociates the effects of response repetition and stimulus repetition. Response repetition alone did not facilitate performance. Stimulus repetition did aid performance, but mainly when accompanied by response repetition. Subjects tended to avoid the normal comparison process by using the (invalid!) “bypass rule” (Fletcher and Rabbitt, 1978): repeat the response if the stimulus or some aspect thereof (letter contents, size, position) is repeated from the preceding trial, otherwise change the response. As to general effects, partial refractoriness was evident at response execution, but not at earlier processing stages. Mean RT increased, but errors decreased, as the response-stimulus interval (RSI) between trials decreased. Presenting a new letter pair immediately after the preceding response produced a delay, but subjects used the waiting time, while the response system recovered or was redirected to the present trial, to improve the accuracy of their decision.


Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1534 ◽  
Author(s):  
Ghazal Rouhafzay ◽  
Ana-Maria Cretu

Drawing inspiration from haptic exploration of objects by humans, the current work proposes a novel framework for robotic tactile object recognition, where visual information in the form of a set of visually interesting points is employed to guide the process of tactile data acquisition. Neuroscience research confirms the integration of cutaneous data as a response to surface changes sensed by humans with data from joints, muscles, and bones (kinesthetic cues) for object recognition. On the other hand, psychological studies demonstrate that humans tend to follow object contours to perceive their global shape, which leads to object recognition. In compliance with these findings, a series of contours are determined around a set of 24 virtual objects from which bimodal tactile data (kinesthetic and cutaneous) are obtained sequentially and by adaptively changing the size of the sensor surface according to the object geometry for each object. A virtual Force Sensing Resistor array (FSR) is employed to capture cutaneous cues. Two different methods for sequential data classification are then implemented using Convolutional Neural Networks (CNN) and conventional classifiers, including support vector machines and k-nearest neighbors. In the case of conventional classifiers, we exploit contourlet transformation to extract features from tactile images. In the case of CNN, two networks are trained for cutaneous and kinesthetic data and a novel hybrid decision-making strategy is proposed for object recognition. The proposed framework is tested both for contours determined blindly (randomly determined contours of objects) and contours determined using a model of visual attention. Trained classifiers are tested on 4560 new sequential tactile data and the CNN trained over tactile data from object contours selected by the model of visual attention yields an accuracy of 98.97% which is the highest accuracy among other implemented approaches.


1982 ◽  
Vol 111 (3) ◽  
pp. 348-368 ◽  
Author(s):  
Peter Walker ◽  
Eileen Marshall

2017 ◽  
Author(s):  
Daniel Feuerriegel ◽  
Owen Churches ◽  
Scott Coussens ◽  
Hannah A. D. Keage

AbstractRepeated stimulus presentation leads to complex changes in cortical neuron response properties, commonly known as repetition suppression or stimulus-specific adaptation. Circuit-based models of repetition suppression provide a framework for investigating patterns of repetition effects that propagate through cortical hierarchies. To further develop such models it is critical to determine whether (and if so, when) repetition effects are modulated by top-down influences, such as those related to perceptual expectation. We investigated this by presenting pairs of repeated and alternating face images, and orthogonally manipulating expectations regarding the likelihood of stimulus repetition. Event-related potentials (ERPs) were recorded from n=39 healthy adults, to map the spatiotemporal progression of stimulus repetition and expectation effects, and interactions between these factors, using mass univariate analyses. We also tested whether the ability to predict unrepeated (compared to repeated) face identities could influence the magnitude of observed repetition effects, by presenting separate blocks with predictable and unpredictable alternating faces. Multiple repetition and expectation effects were identified between 99-800ms from stimulus onset, which did not statistically interact at any point. Repetition effects in blocks with predictable alternating faces were smaller than in unpredictable alternating face blocks between 117-179ms and 506-652ms, and larger between 246-428ms. ERP repetition effects appear not to be modulated by perceptual expectations, supporting separate mechanisms for repetition and expectation suppression. However, previous studies that aimed to test for repetition effects, in which the repeated (but not unrepeated) stimulus was predictable, are likely to have conflated repetition and stimulus predictability effects.Highlights- ERP face image repetition effects were apparent between 99-800ms from stimulus onset- Expectations of stimulus image properties did not modulate face repetition effects- The predictability of unrepeated stimuli influenced repetition effect magnitudes


Neuroreport ◽  
2008 ◽  
Vol 19 (2) ◽  
pp. 161-165 ◽  
Author(s):  
Anthony P. Weiss ◽  
Margaret Duff ◽  
Joshua L. Roffman ◽  
Scott L. Rauch ◽  
Gary E. Strangman

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