Evaluation of disruptive camouflage of avian cup-nests

Parent birds employ various strategies to protect their offspring against nest predators. Two well‐researched anti‐nest‐predation strategies involve visual concealment of the nest by way of parental camouflage and egg camouflage. By contrast, camouflage of nest structures is relatively under‐researched, particularly in the case of cup‐nests in trees and bushes. We explored how birds camouflage cup‐nests in nature. Specifically, we tested Hansell’s hypothesis that birds use externally applied pale and white objects such as spider cocoons and lichens to achieve cup‐nest camouflage. To test Hansell’s hypothesis, three complementary experiments were performed: (1) an in situ nest predation experiment; (2) a photo‐based visual search experiment; and (3) contrast analyses using PAT‐GEOM software in IMAGEJ. White paper and chalk spots were used to mimic white objects used by birds in nature. Whereas predation rates in Experiment 1 were not affected by white spots, location rates in Experiment 2 were lower for natural nests with white spots than without white spots. Experiment 3 demonstrated that white spots significantly increased the contrast between different visual elements of nests. It was concluded that white objects can potentially camouflage nests against some nest predators, and that any improved camouflage was probably achieved via disruptive camouflage.Publisher PDFPeer reviewe

Edge-enhanced disruptive camouflage impairs shape discrimination

Disruptive colouration (DC) is a form of camouflage comprised of areas of pigmentation across a target’s surface that form false edges, which are said to impede detection by disguising the outline of the target. In nature, many species with DC also exhibit edge enhancement (EE); light areas have lighter edges and dark areas have darker edges. EE DC has been shown to undermine not only localisation but also identification of targets, even when they are not hidden (Sharman, Moncrieff, & Lovell, 2018). We use a novel task, where participants judge which “snake” is more “wiggly,” to measure shape discrimination performance for three colourations (uniform, DC, and EE DC) and two backgrounds (leafy and uniform). We show that EE DC impairs shape discrimination even when targets are not hidden in a textured background. We suggest that this mechanism may contribute to misidentification of EE DC targets

Dissociating the effect of disruptive colouration on localisation and identification of camouflaged targets

Disruptive camouflage features contrasting areas of pigmentation across the animals’ surface that form false edges which disguise the shape of the body and impede detection. In many taxa these false edges feature local contrast enhancement or edge enhancement, light areas have lighter edges and dark areas have darker edges. This additional quality is often overlooked in existing research. Here we ask whether disruptive camouflage can have benefits above and beyond concealing location. Using a novel paradigm, we dissociate the time courses of localisation and identification of a target in a single experiment. We measured the display times required for a stimulus to be located or identified (the critical duration). Targets featured either uniform, disruptive or edge enhanced disruptive colouration. Critical durations were longer for identifying targets with edge enhanced disruptive colouration camouflage even when presented against a contrasting background, such that all target types were located equally quickly. For the first time, we establish empirically that disruptive camouflage not only conceals location, but also disguises identity. This shows that this form of camouflage can be useful even when animals are not hidden. Our findings offer insights into how edge enhanced disruptive colouration undermines visual perception by disrupting object recognition

The System Kato: Detecting Cases of Plagiarism for Answer-Set Programs

Plagiarism detection is a growing need among educational institutions and solutions for different purposes exist. An important field in this direction is detecting cases of source-code plagiarism. In this paper, we present the tool Kato for supporting the detection of this kind of plagiarism in the area of answer-set programming (ASP). Currently, the tool is implemented for DLV programs but it is designed to handle other logic-programming dialects as well. We review the basic features of Kato, introduce its theoretical underpinnings, and discuss an application of Kato for plagiarism detection in the context of courses on logic programming at the Vienna University of Technology

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

3D Camouflaging Object using RGB-D Sensors

This paper proposes a new optical camouflage system that uses RGB-D cameras, for acquiring point cloud of background scene, and tracking observers eyes. This system enables a user to conceal an object located behind a display that surrounded by 3D objects. If we considered here the tracked point of observer s eyes is a light source, the system will work on estimating shadow shape of the display device that falls on the objects in background. The system uses the 3d observer s eyes and the locations of display corners to predict their shadow points which have nearest neighbors in the constructed point cloud of background scene.Comment: 6 pages, 12 figures, 2017 IEEE International Conference on SM