We describe new techniques to detect and analyze periodic motion as seen from both a static and a moving camera. By tracking objects of interest, we compute an object's self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic and we apply time-frequency analysis to detect and characterize the periodic motion. The periodicity is also analyzed robustly using the 2D lattice structures inherent in similarity matrices. A real-time system has been implemented to track and classify objects using periodicity. Examples of object classification (people, running dogs, vehicles), person counting, and nonstationary periodicity are provided.

Robust real-time periodic motion detection, analysis, and applications

Underwater imaging is important for scientific research and technology as well as for popular activities, yet it is plagued by poor visibility conditions. In this paper, we present a computer vision approach that removes degradation effects in underwater vision. We analyze the physical effects of visibility degradation. It is shown that the main degradation effects can be associated with partial polarization of light. Then, an algorithm is presented, which inverts the image formation process for recovering good visibility in images of scenes. The algorithm is based on a couple of images taken through a polarizer at different orientations. As a by-product, a distance map of the scene is also derived. In addition, this paper analyzes the noise sensitivity of the recovery. We successfully demonstrated our approach in experiments conducted in the sea. Great improvements of scene contrast and color correction were obtained, nearly doubling the underwater visibility range.

/pdf/recovery-of-underwater-visibility-and-structure-by-246zw4v3ed.pdf

Recovery of underwater visibility and structure by polarization analysis

In optimal foraging theory, search time is a key variable defining the value of a prey type. But the sensory-perceptual processes that constrain the search for food have rarely been considered. Here we evaluate the flight behavior of bumblebees (Bombus terrestris) searching for artificial flowers of various sizes and colors. When flowers were large, search times correlated well with the color contrast of the targets with their green foliage-type background, as predicted by a model of color opponent coding using inputs from the bees' UV, blue, and green receptors. Targets that made poor color contrast with their backdrop, such as white, UV-reflecting ones, or red flowers, took longest to detect, even though brightness contrast with the background was pronounced. When searching for small targets, bees changed their strategy in several ways. They flew significantly slower and closer to the ground, so increasing the minimum detectable area subtended by an object on the ground. In addition, they used a different neuronal channel for flower detection. Instead of color contrast, they used only the green receptor signal for detection. We relate these findings to temporal and spatial limitations of different neuronal channels involved in stimulus detection and recognition. Thus, foraging speed may not be limited only by factors such as prey density, flight energetics, and scramble competition. Our results show that understanding the behavioral ecology of foraging can substantially gain from knowledge about mechanisms of visual information processing.

/pdf/visual-constraints-in-foraging-bumblebees-flower-size-and-29kra3f0j3.pdf

Visual constraints in foraging bumblebees: flower size and color affect search time and flight behavior.

Nearly all animals with good vision have a repertoire of eye movements. The majority show a pattern of stable fixations with fast saccades that shift the direction of gaze. These movements may be made by the eyes themselves, or the head, or in some insects the whole body. The main reason for keeping gaze still during fixations is the need to avoid the blur that results from the long response time of the photoreceptors. Blur begins to degrade the image at a retinal velocity of about 1 receptor acceptance angle per response time. Some insects (e.g. hoverflies) stabilise their gaze much more rigidly than this rule implies, and it is suggested that the need to see the motion of small objects against a background imposes even more stringent conditions on image motion. A third reason for preventing rotational image motion is to prevent contamination of the translational flow-field, by which a moving animal can judge its heading and the distances of objects. Some animals do let their eyes rotate smoothly, and these include some heteropod molluscs, mantis shrimps and jumping spiders, all of which have narrow linear retinae which scan across the surroundings. Hymenopteran insects also rotate during orientation flights at speeds of 100–200° s−1. This is just consistent with a blur-free image, as are the scanning speeds of the animals with linear retinae.

Motion and vision: why animals move their eyes.

The deep sea is the largest habitat on earth. Its three great faunal environments--the twilight mesopelagic zone, the dark bathypelagic zone and the vast flat expanses of the benthic habitat--are home to a rich fauna of vertebrates and invertebrates. In the mesopelagic zone (150-1000 m), the down-welling daylight creates an extended scene that becomes increasingly dimmer and bluer with depth. The available daylight also originates increasingly from vertically above, and bioluminescent point-source flashes, well contrasted against the dim background daylight, become increasingly visible. In the bathypelagic zone below 1000 m no daylight remains, and the scene becomes entirely dominated by point-like bioluminescence. This changing nature of visual scenes with depth--from extended source to point source--has had a profound effect on the designs of deep-sea eyes, both optically and neurally, a fact that until recently was not fully appreciated. Recent measurements of the sensitivity and spatial resolution of deep-sea eyes--particularly from the camera eyes of fishes and cephalopods and the compound eyes of crustaceans--reveal that ocular designs are well matched to the nature of the visual scene at any given depth. This match between eye design and visual scene is the subject of this review. The greatest variation in eye design is found in the mesopelagic zone, where dim down-welling daylight and bio-luminescent point sources may be visible simultaneously. Some mesopelagic eyes rely on spatial and temporal summation to increase sensitivity to a dim extended scene, while others sacrifice this sensitivity to localise pinpoints of bright bioluminescence. Yet other eyes have retinal regions separately specialised for each type of light. In the bathypelagic zone, eyes generally get smaller and therefore less sensitive to point sources with increasing depth. In fishes, this insensitivity, combined with surprisingly high spatial resolution, is very well adapted to the detection and localisation of point-source bioluminescence at ecologically meaningful distances. At all depths, the eyes of animals active on and over the nutrient-rich sea floor are generally larger than the eyes of pelagic species. In fishes, the retinal ganglion cells are also frequently arranged in a horizontal visual streak, an adaptation for viewing the wide flat horizon of the sea floor, and all animals living there. These and many other aspects of light and vision in the deep sea are reviewed in support of the following conclusion: it is not only the intensity of light at different depths, but also its distribution in space, which has been a major force in the evolution of deep-sea vision.

Vision in the deep sea

http://www.springer.de 783540 4045 76 9 ISBN 3-540-40457-0 While the human eye can practically cope only with two aspects of light, brightness and colour, for many animals polarization is a further source of visual information. This fascinating phenomenon of polarization sensitivity is comprehensively treated by Horvath and Varju. Starting with a short introduction into imaging polarimetry – an efficient technique for measuring light polarization – various polarization patterns occurring in nature are presented. Among them are the polarizational characteristics of water surfaces, mirages and the underwater light field as well as the celestial polarization patterns affected by the illumination conditions of sunrise, sunset, clear or cloudy skies, moonshine and total solar eclipses.

Polarized light in animal vision : polarization patterns in nature

The reflection-polarization patterns of small freshwater habitats under clear skies can be recorded by video polarimetry in the red, green and blue ranges of the spectrum. In this paper, the simple technique of rotating-analyzer video polarimetry is described and its advantages and disadvantages are discussed. It is shown that the polarization patterns of small water bodies are very variable in the different spectral ranges depending on the illumination conditions. Under clear skies and in the visible range of the spectrum, flat water surfaces reflecting light from the sky are most strongly polarized in the blue range. Under an overcast sky radiating diffuse white light, small freshwater habitats are characterized by a high level of horizontal polarization at or near the Brewster angle in all spectral ranges except that in which the contribution of subsurface reflection is large. In a given spectral range and at a given angle of view, the direction of polarization is horizontal if the light mirrored from the surface dominates and vertical if the light returning from the subsurface regions dominates. The greater the degree of dominance, the higher the net degree of polarization, the theoretical maximum value being 100 % at the Brewster angle for the horizontal E-vector component and approximately 30 % at flat viewing angles for the vertical E-vector component. We have made video polarimetric measurements of differently coloured fruits and vegetables to demonstrate that polarized light in nature follows this general rule. The consequences of the reflection-polarization patterns of small bodies of water for water detection by polarization-sensitive aquatic insects are discussed.

Polarization pattern of freshwater habitats recorded by video polarimetry in red, green and blue spectral ranges and its relevance for water detection by aquatic insects

Underwater refraction-polarization patterns of skylight perceived by aquatic animals through Snell's window of the flat water surface

1.

While collecting nectar in hovering flight the European hawk moth Macroglossum stellatarum efficiently regulates its distance relative to flowers that are shaken by wind. This can be demonstrated in laboratory experiments by moving dummy flowers (blue cardboard disks) towards and away from the feeding animal (Fig. 1).




2.

Distance regulation is predominantly mediated by visual cues. Mechanoreceptors on the proboscis appear to contribute little to the response.




3.

Movements of dummy flowers can be simulated by expanding and contracting a pattern projected onto a screen. With this technique we investigated the dynamical properties of the servo mechanism underlying distance regulation. The system behaves as a bandpass filter with corner frequencies of 0.15 and 5 Hz (Figs.2,3).




4.

When a high-speed ramp-like movement of the flower is simulated, there is an asymmetry in the response. During simulated approach the reaction is phasic-tonic with a pronounced overshoot at the beginning, during simulated retraction it remains tonic (Fig.5B,C).




5.

During distance regulation the animals compensate for the speed of the edge of the projected pattern. Distance regulation improves substantially when the number of stimulated elementary movement detectors is increased through increasing the number of contour lines by projecting concentric rings instead of a homogeneous disk (Figs.7, 8).

The regulation of distance to dummy flowers during hovering flight in the hawk moth Macroglossum stellatarum

1.

Foraging bees return to their hive with partially filled honey sack. We have re-evaluated previously published data and propose a mathematical model to describe the take-off crop load as a function of the flow rate v and the concentration c of sugar solution.




2.

The model has been derived on the basis of one set of experiments (Fig. 1). It describes the results of other investigations under quite different experimental conditions.




3.

We discuss, whether the bees' partial crop filling optimizes the relation between gained and consumed energy during foraging, or whether they are driven by an information demand which can be satisfied by returning to the hive with partially filled crop. The former is favoured by several authors seeking support for optimality theories in evolution.




4.

We arrive at the conclusion that all experimental results can satisfactorily be explained without the energy balance hypothesis.

Dezsö Varjú

Papers

Polarized light in animal vision : polarization patterns in nature

Polarization pattern of freshwater habitats recorded by video polarimetry in red, green and blue spectral ranges and its relevance for water detection by aquatic insects

Underwater refraction-polarization patterns of skylight perceived by aquatic animals through Snell's window of the flat water surface

The regulation of distance to dummy flowers during hovering flight in the hawk moth Macroglossum stellatarum

What do foraging honeybees optimize