Survey of Object Detection Methods in Camouflaged Image

Camouflage is an attempt to conceal the signature of a target object into the background image. Camouflage detection methods or Decamouflaging method is basically used to detect foreground object hidden in the background image. In this research paper authors presented survey of camouflage detection methods for different applications and areas

Establishing the behavioural limits for countershaded camouflage

Countershading is a ubiquitous patterning of animals whereby the side that typically faces the highest illumination is darker. When tuned to specific lighting conditions and body orientation with respect to the light field, countershading minimizes the gradient of light the body reflects by counterbalancing shadowing due to illumination, and has therefore classically been thought of as an adaptation for visual camouflage. However, whether and how crypsis degrades when body orientation with respect to the light field is non-optimal has never been studied. We tested the behavioural limits on body orientation for countershading to deliver effective visual camouflage. We asked human participants to detect a countershaded target in a simulated three-dimensional environment. The target was optimally coloured for crypsis in a reference orientation and was displayed at different orientations. Search performance dramatically improved for deviations beyond 15 degrees. Detection time was significantly shorter and accuracy significantly higher than when the target orientation matched the countershading pattern. This work demonstrates the importance of maintaining body orientation appropriate for the displayed camouflage pattern, suggesting a possible selective pressure for animals to orient themselves appropriately to enhance crypsis

e-SNLI: Natural Language Inference with Natural Language Explanations

In order for machine learning to garner widespread public adoption, models must be able to provide interpretable and robust explanations for their decisions, as well as learn from human-provided explanations at train time. In this work, we extend the Stanford Natural Language Inference dataset with an additional layer of human-annotated natural language explanations of the entailment relations. We further implement models that incorporate these explanations into their training process and output them at test time. We show how our corpus of explanations, which we call e-SNLI, can be used for various goals, such as obtaining full sentence justifications of a model's decisions, improving universal sentence representations and transferring to out-of-domain NLI datasets. Our dataset thus opens up a range of research directions for using natural language explanations, both for improving models and for asserting their trust.Comment: NeurIPS 201

Camouflage in predators

Camouflage – adaptations that prevent detection and/or recognition – is a key example of evolution by natural selection, making it a primary focus in evolutionary ecology and animal behaviour. Most work has focused on camouflage as an anti‐predator adaptation. However, predators also display specific colours, patterns and behaviours that reduce visual detection or recognition to facilitate predation. To date, very little attention has been given to predatory camouflage strategies. Although many of the same principles of camouflage studied in prey translate to predators, differences between the two groups (in motility, relative size, and control over the time and place of predation attempts) may alter selection pressures for certain visual and behavioural traits. This makes many predatory camouflage techniques unique and rarely documented. Recently, new technologies have emerged that provide a greater opportunity to carry out research on natural predator–prey interactions. Here we review work on the camouflage strategies used by pursuit and ambush predators to evade detection and recognition by prey, as well as looking at how work on prey camouflage can be applied to predators in order to understand how and why specific predatory camouflage strategies may have evolved. We highlight that a shift is needed in camouflage research focus, as this field has comparatively neglected camouflage in predators, and offer suggestions for future work that would help to improve our understanding of camouflage.Publisher PDFPeer reviewe