Image Processing Test Bench for Robot Vision Using C#

Purpose: Nowadays, image processing is a well-known technological term. In some of the industries, it has practical needs. It is an essential tool for the process and robotic industry. Various popular frameworks and libraries are available to process the image. The OpenCV is one of the best and popular libraries for image processing. It was originally written in C++ by Intel. Now various wrappers are available to implement into the different programming languages. The OpenCvSharp is the wrapper of OpenCV. Those who are familiar with C# can use it. The new researcher who wants to integrate image processing into their project takes some time for setup, function writing, and integration. Here we created a test bench application for Image processing demonstration. It has been made with some usual function to process the image. It was created using visual studio 2022 and OpenCvSharp wrapper in C# language. The researcher can learn about various image processing algorithms without writing any code or giving little bits of effort. The complete project is available on GitHub. Anyone can download, experiment, and integrate into their project without any issue. Design/Methodology/Approach: We created a GUI (Graphical User Interface) based C# application. Using Nuget Package manager, installed two OpenCV wrapper packages. To invoke several functions, we add some buttons, and for changing the method’s parameter, we integrate some text boxes. We created some abstraction layers Between the OpenCvSharp wrapper and GUI. We made our custom module as portable as possible so that our researchers could easily incorporate it into their project. Findings/result: This unique image processing test bench is designed for new researchers trying to integrate image processing capability into their research work. It can take still images or moving images through the connected webcam, automatically sending the various commands and promptly observing the result. Originality/Value: This test bench has been arranged uniquely for the researcher. It might have some value to their research work. The unique feature like automatic trigger can help them send the series of commands without repeatedly typing or pressing the button to see the result. Paper Type: Experiment-based Research

Who’s Getting a Head Start? Mesocephalic Dogs in Still Images Are Attributed More Positively Valenced Emotions Than Dogs of Other Cephalic Index Groups

Assumptions about dogs’ personality are influenced by their appearance, which may lead to differences in ownership styles and subsequent canine welfare. The influence of canine appearance on observers’ emotion attributions to dogs remains largely unexplored. This study investigated whether canine head shape is related to how both dog owners and non-dog owning adults in the U.K. attribute emotions to still images of dogs, and in the case of dog owners, to their own dogs. Attachment, respondent personality and dog trainability were assessed as potential influences on emotional attribution in owners. Overall, 2451 participant responses were received. Still images of mesocephalic dogs were attributed primary and positively valenced emotion with more strength and frequency than other groups. Mesocephalic images were also attributed negatively valenced emotions less frequently and with less strength than other groups. Apart from empathy, no significant differences were found in emotional attribution to owned dogs of different head shapes; however, human personality influenced attribution of emotions to owned dogs. The finding that some dogs are attributed emotions more readily based on their appearance alone has applied importance, given, for example, the potential for misattribution of positive emotions to dogs in negative emotional states, and potential prejudice against dogs considered in negative emotional states.

A difficult history of light. About metaphysical ideas of “light writing” formulated before the birth of photography

The reflections presented in this article are devoted to Junko Theresa Mikuriya’s book, A History of Light. The Idea of Photography. It is a unique view on the search for pre-photographic origins of photography in the field of philosophical writings ranging from Plato, through the neoplatonic philosopher Jamblich’s enquiry, to the texts by Philotheus of Batos and by an early Renaissance philosopher, Marsilio Ficino. When thinking about metaphysics present in (moving and still) images, one should not forget about the metaphysics of the image itself. The idea of photography – regardless of whether we are witnessing a fundamental change in an ontological transition from an analogue to a digital form of image recording – obliges us to discuss the “history of light”, as this is what Mikuriya does. While locating the discussed concepts in the context of the history and theory of photography, as well as the archaeology of media, the author of this essay engages in a dialogue with Mikuriya and polemically discusses many of her hypotheses. Key concepts such as chalepon, photagogia, triton genos, phôteinographeisthai are analysed in order to indicate inspiring moments in the Mikuriya’s reflections, but also a kind of interpretive abuse in the process of reading and analysing philosophical texts addressing the issues of light.

The use of a long-acting tranquilizer (zuclopenthixol acetate) and live video monitoring for successful long-distance transport of caribou (Rangifer tarandus)

Long-distance transport of caribou (Rangifer tarandus) can result in morbidities and mortalities. This case report describes the use of a long-acting tranquilizer, zuclopenthixol acetate (ZA) and live video monitoring (LVM) to transport caribou over 2300 kilometers. Two groups of captive caribou were transported from Fort St. John, British Columbia to Dryden, Ontario (n=14; 28.5 h transport) and Anchorage, Alaska (n=11; 32 h transport). The day prior to transport, caribou were administered ZA at 1 mg/kg via deep intramuscular (IM) injection. Digital video cameras allowed for live observation of caribou during transport. Still images of videos from each compartment in the Ontario transport were analyzed for percentage (%) lying versus standing over three time periods (Day 1, Night, and Day 2). Overall, caribou spent 57% of the transport lying down, with the highest percentage occurring at night (73%). As group size and animal density decreased there was a trend for caribou to spend more time lying down. Three animals developed extrapyramidal effects to the ZA and were effectively treated with midazolam at 0.2 mg/kg IM. There were no significant visible injuries or mortalities during or up to 6 weeks post-transport. Zuclopenthixol acetate and LVM were used to successfully transport caribou over long distances and should be considered in future translocations to improve animal welfare during transport.

Crowdsourcing Documentary Making

The creative commons documentary Preempting Dissent (2014) builds upon the book of the same name written by Greg Elmer and Andy Opel. The film is a culmination of a collaborative process of soliciting, collecting and editing video, still images, and creative commons music files from people around the world. Preempting Dissent interrogates the expansion of the so-called “Miami-Model” of protest policing, a set of strategies developed in the wake of 9/11 to preempt forms of mass protest at major events in the US and worldwide. The film tracks the development of the Miami model after the WTO protests in Seattle 1999, through the post-9/11 years, FTAA & G8/20 summits, and most recently the Occupy Wall St movements. The film exposes the political, social, and economic roots of preemptive forms of protest policing and their manifestations in spatial tactics, the deployment of so-called ‘less-lethal’ weapons, and surveillance regimes. The film notes however that new social movements have themselves begun to adopt preemptive tactics so as not to fall into the trap set for them by police agencies worldwide.

When Imagery and Physical Sampling Work Together: Toward an Integrative Methodology of Deep-Sea Image-Based Megafauna Identification

Imagery has become a key tool for assessing deep-sea megafaunal biodiversity, historically based on physical sampling using fishing gears. Image datasets provide quantitative and repeatable estimates, small-scale spatial patterns and habitat descriptions. However, taxon identification from images is challenging and often relies on morphotypes without considering a taxonomic framework. Taxon identification is particularly challenging in regions where the fauna is poorly known and/or highly diverse. Furthermore, the efficiency of imagery and physical sampling may vary among habitat types. Here, we compared biodiversity metrics (alpha and gamma diversity, composition) based on physical sampling (dredging and trawling) and towed-camera still images (1) along the upper continental slope of Papua New Guinea (sedimented slope with wood-falls, a canyon and cold seeps), and (2) on the outer slopes of the volcanic islands of Mayotte, dominated by hard bottoms. The comparison was done on selected taxa (Pisces, Crustacea, Echinoidea, and Asteroidea), which are good candidates for identification from images. Taxonomic identification ranks obtained for the images varied among these taxa (e.g., family/order for fishes, genus for echinoderms). At these ranks, imagery provided a higher taxonomic richness for hard-bottom and complex habitats, partially explained by the poor performance of trawling on these rough substrates. For the same reason, the gamma diversity of Pisces and Crustacea was also higher from images, but no difference was observed for echinoderms. On soft bottoms, physical sampling provided higher alpha and gamma diversity for fishes and crustaceans, but these differences tended to decrease for crustaceans identified to the species/morphospecies level from images. Physical sampling and imagery were selective against some taxa (e.g., according to size or behavior), therefore providing different facets of biodiversity. In addition, specimens collected at a larger scale facilitated megafauna identification from images. Based on this complementary approach, we propose a robust methodology for image-based faunal identification relying on a taxonomic framework, from collaborative work with taxonomists. An original outcome of this collaborative work is the creation of identification keys dedicated specifically to in situ images and which take into account the state of the taxonomic knowledge for the explored sites.

Retail Florists Use Novel Sales Approaches during the COVID-19 Pandemic

Retail florists in the United States were surveyed from Oct. to Nov. 2020 to document business practices and innovative approaches to marketing, designing, and delivering flowers during Mar. to Sept. 2020 of the coronavirus disease (COVID-19) pandemic. Slightly less than half of the responding florists (45.0%) closed operations for an average of 31 to 60 days (15.6%). City or county COVID-19 restrictions caused 34% to close their storefronts to customers. Nearly all offered no-contact delivery service. Approximately one-third of these florists used social media marketing consisting of still images and video posts, and a similar number offered no-contact shopping options. Two-thirds of the florists made no changes to the way they designed flowers (60.6%). Event-oriented stores reorganized their business models and sought daily work to replace postponed or canceled wedding orders. Three-fourths of the florists who terminated employees because of shutdowns hired or planned to rehire all terminated employees.

Real-Time Mask Recognition

While a variety of image processing studies have been performed to quantify the potential performance of neural network-based models using high-quality still images, relatively few studies seek to apply those models to a real-time operational context. This paper seeks to extend prior work in neural-network-based mask detection algorithms to a real-time, low-power deployable context that is conducive to immediate installation and use. Particularly relevant in the COVID-19 era with varying rules on mask mandates, this work applies two neural network models to inference of mask detection in both live (mobile) and recorded scenarios. Furthermore, an experimental dataset was collected where individuals were encouraged to use presentation attacks against the algorithm to quantify how perturbations negatively impact model performance. The results from evaluation on the experimental dataset are further investigated to identify the degradation caused by poor lighting and image quality, as well as to test for biases within certain demographics such as gender and ethnicity. In aggregate, this work validates the immediate feasibility of a low-power and low-cost real-time mask recognition system.

Novel objects with causal schemas elicit selective responses in tool- and hand-selective lateral occipito-temporal cortex

Tool-selective lateral occipito-temporal cortex (LOTC) responds preferentially to images of tools (hammers, brushes) relative to non-tool objects (clocks, shoes). What drives these responses? Tools have elongated shapes and are more likely to have motor associations, but another essential property is that they exert causal effects on the environment. We tested whether LOTC would respond to novel objects associated with a tool-canonical schema in which their actions cause other events. To do so, we taught male and female human participants about novel objects embedded in animated event sequences, which varied in the temporal order of their events. Causer objects moved prior to the appearance of an environmental event (e.g., stars) while Reactor objects moved after an identical event; objects were matched on shape and motor association. During fMRI, participants viewed still images of these novel objects. We localized tool-selective LOTC and non-tool-selective parahippocampal cortex (PHC) by contrasting neural responses to images of familiar tools and non-tools. We found that LOTC responded more to Causers than Reactors; this effect was absent and weaker in right PHC. We also localized responses to images of hands, which elicit overlapping responses with tools. Across inferior temporal cortex, voxels’ tool and hand selectivity positively predicted a preferential response to Causers, and non-tool selectivity negatively so. We conclude that a causal schema typical of tools is sufficient to drive LOTC, and more generally, that preferential responses to domains across the temporal lobe may reflect the relational event structures typical of those domains.