1,721,209 research outputs found
An insect inspired object tracking mechanism for autonomous vehicles
No full textZahra Bagheri, Benjamin S. Cazzolato, Stevend D. Wiederman, Steven Grainger, and David C. O'Carrol
Wiederman SD, PhD Thesis
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<p>Some insects have the capability to detect and track small moving objects, often against cluttered moving backgrounds. Determining how this task is performed is an intriguing challenge, both from a physiological and computational perspective. Previous research</p>
<p>has characterized higher-order neurons within the fly brain known as ‘small target motion detectors’ (STMD) that respond selectively to targets, even within complex moving surrounds. Interestingly, these cells still respond robustly when the velocity of the target is matched to the velocity of the background (i.e. with no relative motion cues).</p>
<p>We performed intracellular recordings from intermediate-order neurons in the fly visual system (the medulla). These full-wave rectifying, transient cells (RTC) reveal independent adaptation to luminance changes of opposite signs (suggesting separate ‘on’ and ‘off’ channels) and fast adaptive temporal mechanisms (as seen in some previously described cell types). We show, via electrophysiological experiments, that the RTC is temporally responsive to rapidly changing stimuli and well suited along a proposed pathway to target-detecting neurons.</p>
<p>To model this target discrimination, we use high dynamic range (HDR) natural images to represent ‘real-world’ luminance values that serve as inputs to a biomimetic representation of photoreceptor processing. Adaptive spatiotemporal high-pass filtering (1st-order interneurons) shape the transient ‘edge-like’ responses, useful for feature discrimination. Following this, a model for the RTC implements a nonlinear facilitation between the rapidly adapting, and independent polarity contrast channels, each with center-surround antagonism. The recombination of the channels results in increased discrimination of small targets, of approximately the size of a single pixel, without the</p>
<p>need for relative motion cues. This method of feature discrimination contrasts with traditional target and background motion-field computations. We show that our RTC based target detection model is well matched to properties described for the higher order STMD neurons, such as contrast sensitivity, height tuning and velocity tuning.</p>
<p>The model output shows that the spatiotemporal profile of small targets is sufficiently rare within natural scene imagery to allow our highly nonlinear ‘matched filter’ to successfully detect many targets from the background. The model produces robust target discrimination across a biologically plausible range of target sizes and a range of velocities. We show that the model for small target motion detection is highly correlated to the velocity of the stimulus but not other background</p>
<p>statistics, such as local brightness or local contrast, which normally influence target detection tasks.</p>
<p>From an engineering perspective, we examine model elaborations for improved target discrimination via inhibitory interactions from correlation-type motion detectors, using a form of antagonism between our feature correlator and the more typical motion correlator. We also observe that a changing optimal threshold is highly correlated to the</p>
<p>value of observer ego-motion. We present an elaborated target detection model that allows for implementation of a static optimal threshold, by scaling the target discrimination mechanism with a model-derived velocity estimation of ego-motion.</p>
<p>Finally, we investigate the physiological relevance of this target discrimination model. We show that via very subtle image manipulation of the visual stimulus, our model accurately predicts dramatic changes in observed electrophysiological responses from STMD neurons.</p
ACRA_files_2018_and_2019.zip
No full textScripts and supporting files underlying:
J. V. James, B. S. Cazzolato, S. Grainger, D. C. O’Carroll, and S. D. Wiederman, “An insect-inspired detection algorithm for aerial drone detection,” in Australasian Conference on Robotics and Automation (ACRA), Australian Robotics and Automation Association, 2018, pp. 1–9. [Online]. Available: https://ssl.linklings.net/conferences/acra/acra2018_proceedings/views/includes/files/pap120s1-file1.pdf
and
J. V. James, B. S. Cazzolato, S. Grainger, and S. D. Wiederman, “A probabilistic tracker for a bio-inspired target detection algorithm,” in Australasian Conference on Robotics and Automation (ACRA), Australian Robotics and Automation Association, 2019, pp. 1–10. [Online]. Available: https://ssl.linklings.net/conferences/acra/acra2019proceedings/views/includes/files/pap149s1-file1.pdf</p
Discrimination of features in natural scenes by a dragonfly neuron
Full text linkFlying insects engage in spectacular high-speed pursuit of targets, requiring visual discrimination of moving objects against cluttered backgrounds. As a first step toward understanding the neural basis for this complex task, we used computational modeling of insect small target motion detector (STMD) neurons to predict responses to features within natural scenes and then compared this with responses recorded from an identified STMD neuron in the dragonfly brain (Hemicordulia tau). A surprising model prediction confirmed by our electrophysiological recordings is that even heavily cluttered scenes contain very few features that excite these neurons, due largely to their exquisite tuning for small features. We also show that very subtle manipulations of the image cause dramatic changes in the response of this neuron, because of the complex inhibitory and facilitatory interactions within the receptive field.Steven D. Wiederman and David C. O'Carrol
ACRA_files_2018_and_2019.zip
No full text<p>Scripts and supporting files underlying:</p>
<p>J. V. James, B. S. Cazzolato, S. Grainger, D. C. O’Carroll, and S. D. Wiederman, “An insect-inspired detection algorithm for aerial drone detection,” in Australasian Conference on Robotics and Automation (ACRA), Australian Robotics and Automation Association, 2018, pp. 1–9. [Online]. Available: https://ssl.linklings.net/conferences/acra/acra2018_proceedings/views/includes/files/pap120s1-file1.pdf</p>
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<p>J. V. James, B. S. Cazzolato, S. Grainger, and S. D. Wiederman, “A probabilistic tracker for a bio-inspired target detection algorithm,” in Australasian Conference on Robotics and Automation (ACRA), Australian Robotics and Automation Association, 2019, pp. 1–10. [Online]. Available: https://ssl.linklings.net/conferences/acra/acra2019proceedings/views/includes/files/pap149s1-file1.pdf</p>
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Can a competitive neural network explain selective attention in insect target tracking neurons?
No full textSmall target motion detecting (STMD) neurons in the dragonfly brain are neural correlates of a highly-specialized and ethologically-significant feature detection function, and the recent discovery of selective attention in STMDs has clear implications for the ability of dragonflies to track and pursue one target from among several. We used a biophysically-plausible neural network model, based on competitive units fed by NMDA-type synaptic inputs and including lateral feedback inhibition, to model these attentional effects in numerical simulations. With appropriate forward gain, the model displays a winner-takes-all behavior that partially captures the selective attention documented in electrophysiological recordings from STMDs. It cannot, however, explain the full range of results that have now been observed in wide-field STMDs, in particular a bias toward attention to targets dependent on their traversal of continuous trajectories.Patrick A. Shoemaker, Steven D. Wiederman, and David C. O’Carrol
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