Object Detection Using an Ideal Observer Model

2020 ◽  
Vol 2020 (16) ◽  
pp. 41-1-41-7
Author(s):  
Orit Skorka ◽  
Paul J. Kane
Keyword(s):  
Object Detection ◽  
Matched Filter ◽  
Image Sensors ◽  
Ideal Observer ◽  
Noise Power ◽  
Relative Evaluation ◽  
Detection And Identification ◽  
Cross Correlation Analysis ◽  
Observer Model ◽  
The Ideal

Many of the metrics developed for informational imaging are useful in automotive imaging, since many of the tasks – for example, object detection and identification – are similar. This work discusses sensor characterization parameters for the Ideal Observer SNR model, and elaborates on the noise power spectrum. It presents cross-correlation analysis results for matched-filter detection of a tribar pattern in sets of resolution target images that were captured with three image sensors over a range of illumination levels. Lastly, the work compares the crosscorrelation data to predictions made by the Ideal Observer Model and demonstrates good agreement between the two methods on relative evaluation of detection capabilities.

Addition of a channel mechanism to the ideal-observer model

1987 ◽  
Vol 4 (12) ◽  
pp. 2447 ◽  
Author(s):  
Kyle J. Myers ◽  
Harrison H. Barrett
Keyword(s):  
Ideal Observer ◽  
Observer Model ◽  
The Ideal

scholarly journals Contrasting RNN-based and simulation-based models of human physical parameter inference

2020 ◽  
Author(s):  
Héctor Otero Mediero ◽  
Neil R Bramley
Keyword(s):  
Mental Simulation ◽  
Ideal Observer ◽  
Reasoning Task ◽  
Parameter Inference ◽  
Human Errors ◽  
Passive Condition ◽  
Simulation Based ◽  
Observer Model ◽  
Cognitive Plausibility ◽  
The Ideal

A number of recent studies have used ideal observer models to capture human physical learning and reasoning as based on approximate mental simulation. While these approaches can match human competence in specific tasks, they are still relatively far from cognitive plausibility and are limited in their ability to capture patterns of human errors. In the current work, we train a recurrent neural network on the same physical reasoning task explored in Bramley, Gerstenberg, Tenenbaum, and Gureckis (2018) (passive condition), finding a closer match to human patterns than the ideal observer model previously used to make sense of the human judgement patterns.

scholarly journals Tactile orientation perception: an ideal observer analysis of human psychophysical performance in relation to macaque area 3b receptive fields

2015 ◽  
Vol 114 (6) ◽  
pp. 3076-3096 ◽  
Author(s):  
Ryan M. Peters ◽  
Phillip Staibano ◽  
Daniel Goldreich
Keyword(s):  
Cortical Neurons ◽  
Human Performance ◽  
Spatial Perception ◽  
Receptive Fields ◽  
Human Perception ◽  
Ideal Observer ◽  
Orientation Discrimination ◽  
Orientation Perception ◽  
Area 3B ◽  
The Ideal

The ability to resolve the orientation of edges is crucial to daily tactile and sensorimotor function, yet the means by which edge perception occurs is not well understood. Primate cortical area 3b neurons have diverse receptive field (RF) spatial structures that may participate in edge orientation perception. We evaluated five candidate RF models for macaque area 3b neurons, previously recorded while an oriented bar contacted the monkey's fingertip. We used a Bayesian classifier to assign each neuron a best-fit RF structure. We generated predictions for human performance by implementing an ideal observer that optimally decoded stimulus-evoked spike counts in the model neurons. The ideal observer predicted a saturating reduction in bar orientation discrimination threshold with increasing bar length. We tested 24 humans on an automated, precision-controlled bar orientation discrimination task and observed performance consistent with that predicted. We next queried the ideal observer to discover the RF structure and number of cortical neurons that best matched each participant's performance. Human perception was matched with a median of 24 model neurons firing throughout a 1-s period. The 10 lowest-performing participants were fit with RFs lacking inhibitory sidebands, whereas 12 of the 14 higher-performing participants were fit with RFs containing inhibitory sidebands. Participants whose discrimination improved as bar length increased to 10 mm were fit with longer RFs; those who performed well on the 2-mm bar, with narrower RFs. These results suggest plausible RF features and computational strategies underlying tactile spatial perception and may have implications for perceptual learning.

Feature extraction method based on the ideal observer

2001 ◽  
Author(s):  
Hongbin Zhang ◽  
Eric Clarkson ◽  
Harrison H. Barrett
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Ideal Observer ◽  
Feature Extraction Method ◽  
The Ideal

scholarly journals How Optimal is Word-Referent Identification Under Multimodal Uncertainty?

2018 ◽  
Author(s):  
Abdellah Fourtassi ◽  
Michael C. Frank
Keyword(s):  
Visual Cues ◽  
Word Meaning ◽  
Spoken Word ◽  
Ideal Observer ◽  
Optimal Model ◽  
Sources Of Uncertainty ◽  
Multimodal Information ◽  
Model Predictions ◽  
Observer Model ◽  
Novel Words

Identifying a spoken word in a referential context requires both the ability to integrate multimodal input and the ability to reason under uncertainty. How do these tasks interact with one another? We study how adults identify novel words under joint uncertainty in the auditory and visual modalities and we propose an ideal observer model of how cues in these modalities are combined optimally. Model predictions are tested in four experiments where recognition is made under various sources of uncertainty. We found that participants use both auditory and visual cues to recognize novel words. When the signal is not distorted with environmental noise, participants weight the auditory and visual cues optimally, that is, according to the relative reliability of each modality. In contrast, when one modality has noise added to it, human perceivers systematically prefer the unperturbed modality to a greater extent than the optimal model does. This work extends the literature on perceptual cue combination to the case of word recognition in a referential context. In addition, this context offers a link to the study of multimodal information in word meaning learning.

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