Reviewerly/exHarmony huggingface dataset:
A computer-vision based approach to co-register frames from egocentric video recordings

Wearable eye-trackers enable us to record eye movement dynamics from an egocentric viewpoint. Although the data collected from wearable eye-trackers can index our looking patterns in naturalistic settings, current data analyses focus on the correspondence between fixation locations and an individual frame from the egocentric video recording. This analysis approach separates the continuous eye movement dynamics into isolated frames, thereby hindering the study of the temporal dynamics of eye movement patterns, such as building computational models to predict eye movement during interpersonal interactions. The challenges are largely caused by the fact that the recorded eye movement data includes both eye movement and head/body motion, but there is no reliable method to isolate the head/body motion. Therefore, separating eye movement from and head/body motion may potentially facilitate computational models to focus on finding features relevant for predicting fixation dynamics. To this end, we adopt methods in computer vision to correct observers’ head/body motion by co-registering frames of videos taken by head-mounted cameras. The end results are a series of images as if taken from a static camera. Towards this goal, we first used semantic segmentation algorithms based on deep learning to identify stationary objects (e.g., a table & wall) in each frame. Next, we calculated the dense optic flows between every two consecutive frames based on the pixels automatically selected from the stationary objects. The global frame-by-frame movement is then estimated as a series of affine transformations and is used to warp and align consecutive frames. We tested our method on eye-tracking data and egocentric videos simultaneously recorded by head-mounted cameras from infants aged 9-18 months exploring a lab environment. Ongoing works are testing existing models of saliency prediction on the aligned videos.
Detailed memory for visual scenes: remembering a few scenes with a great effort

When studying visual memory for complex scenes, previous research has shown that humans can recognize a large number of previously presented photographs. However, what do we actually remember of each scene? Typical designs present participants with a large set of stimuli and query each scene only once. This approach limits the possibility to measure which individual details are retained in the memory. In our novel paradigm (denoted as intensive memory), we presented participants (N=33) with only three images and they studied each image intensively for three minutes. After learning, we queried each scene 21 times in a 2AFC manner showing two images (one was the original one, the other one contained one photoshopped change) with only a small area showing the original image. The rest of the image was desaturated and blurred to reduce the effect of relearning. This task was counterbalanced within-subject with a typical visual memory task (denoted as extensive memory) in which participants memorized 104 scenes and were tested in 2AFC with 52 pairs of scenes. The accuracy in both tasks correlated (r = .39). In extensive memory, participants reached high accuracy (mean=.89, SD = .08) compared to the intensive memory condition (mean= .64, SD = .08). Further rating of the changes showed that removing an object and changing color were the easiest to recognize and the size of the change was not related to recognition accuracy. Additionally, the difficulty of the task was not related to the perceptual difficulty to detect the change when the original and modified image were presented together. These results show that although it is easy to correctly mark a scene as previously seen in a recognition task, the amount of information people store about each picture is considerably lower, making judgements about scene parts difficult.
Neural networks vs. humans in assessing trademark similarities

Global trademark applications have risen by approx. 46% from 2017 to 2020, according to the World Intellectual Property Organization. As the primary source of visibility for companies, a trademark symbolizes the company’s identity to distinguish itself. Therefore, similarity and confusion are always an issue that raises intellectual property issues. Here, we evaluate the consistency and appropriateness of professional trademark examiners’ judgment on image similarity. First, we use a machine learning approach. We utilize the database provided by the Japan Patent Office for the open online competition “AI x Trademark: Image Search Competition (Detect similar trademark images)” (scheduled on 11/26/2021 to 1/31/2022) to train the DNN to mimic the real judgment records. The database contains images that were judged to be similar in appearance by an officer in real trademark examinations. Using officers’ past judgments as the “ground truth”, we use 2311 pairs of identical trademark images that are judged as similar into the DNN and then test them on 1542 pairs to build a classifier system for trademark similarity judgment. Using the resulting classification, we assess the variability and consistency of professional reviewers’ past decisions. There is consistency, as well as some “oddballs” (i.e., cases with discrepancy), providing hints towards an optimized, hybrid AI decision aid. Next, our psychophysical tests with naïve observers further reveal differences between professional and naïve judgments on image similarity. Thus, we provide an objective machine framework based on which we can evaluate both professional and amateur reviewers’ performances.
Is There One “Beam” of Attention for Searching in Space and Time?

In their pure forms, searching in space entails the allocation of attention to items distributed in space and presented at the same time whereas searching in time entails the allocation of attention to items distributed in time and presented at the same location. In two quite independent projects we have explored whether the metaphorical “beams” operating the domains of space and time might be independent or the same. In one project we used a differential approach. Early research using spatial (Snyder, 1972) and temporal search tasks (McLean, Broadbent & Broadbent, 1983) reported a substantial degree of sloppiness (binding errors). We had participants perform both of these tasks to see if the frequency of these binding errors in the domains of space and time might be correlated. We replicated both early findings of binding errors in space and in time, but their frequency of occurrence in the two domains was not significantly correlated. In the other project, we used an experimental approach. Here we explored whether the principles described by Duncan & Humphreys (1989; hereafter D&H) for searching in space would apply similarly to searching in time. Not surprisingly, performance in spatial search conformed to the predictions of D&H's principles. Importantly, temporal search performance followed the same pattern, suggesting that D&H’s principles are indeed generalizable to temporal search. We will speculate on why these two approaches seem to yield different answers to the question posed in our title.
Validation of a Mouse-Contingent Bi-Resolution Display to measure attention in online videos

Many researchers are currently studying attention online, but have limited options for studying attention to dynamic video stimuli. Webcam-based eye tracking is improving, but is not yet accurate enough for many researchers’ needs. We offer a Mouse-Contingent Bi-Resolution Display (MCBRD) paradigm to measure attention to video in online experiments. In this paradigm, a circular high-resolution window is centered on the viewers’ mouse location, while the rest of the stimulus is presented at a lower resolution. The viewer can view different content by moving the high-resolution window with their mouse. Through this, mouse movements provide an approximation of eye movements and the attended location on the screen. This method, implemented in JavaScript, is one of the first to allow for video stimuli presented with a blurred periphery. By comparing these mouse movement results to eye movements collected from viewers watching 27 videos from the DIEM dataset, we aim to validate the MCBRD as a measure of attention, and determine the optimal blur and window radius settings to use when conducting mouse-contingent display studies with video stimuli. This validation tests window radii of 1.5, 3, and 4.5 degrees of visual angle, and Gaussian blur sigmas of 0.1, 0.3, and 0.5 degrees in a 3x3 within-subjects factorial design. A dynamic screen scaling method is used to present stimuli calibrated for visual angle relatively accurately to online participants. Preliminary analyses show mouse movements from this paradigm are similar to eye movements in terms of on-screen distance explored and areas of interest visited. Current analyses address the blur and window settings that produce mouse movements most similar to eye movements, measured with Normalized Scanpath Similarity and Dynamic Areas of Interest analyses. These validation results will help guide anyone wanting to use a mouse-contingent display to research attention to videos in online studies.
Absolute phase retrieval based on the sinusoidal codewords

Minimizing the number of projecting patterns has been one of the most significant tasks in the field of phase-shifting profilometry. This paper proposes a projecting model of three phase-shifting patterns + one coded pattern to retrieve the absolute phase when measuring the object with isolated surfaces. Differing from the conventional stair-shaped codewords, the proposed sinusoidal codewords are extracted from phase-shifting patterns, and then successively encoded into different periods of one coded pattern. When decoding, four patterns provide one conventional wrapped phase with high precision and six coded phases to determine fringe order. After expanding fringe order, absolute phase can be calculated point-to-point. Experimental results demonstrate that the proposed approach can achieve a considerable measuring accuracy on the dynamic scene.
Design and Implementation of a Smart Healthcare System Using Blockchain Technology with A Dragonfly Optimization-based Blowfish Encryption Algorithm

Because the worth of our health is incalculable, healthcare is one of the most important aspects of our life. However, the present healthcare system lacks excellent service, availability, and convenience of use. Because of its benefits like crypto-security, transparency, data integrity, and a decentralized data network, blockchain technology has been shown to be applicable in almost every field. A smart healthcare system with a blockchain data network delivers transparency, quick and faster access, privacy, reliability, and more in today’s world. This chapter proposes a blockchain based smart healthcare system. Here we use smart contracts for validating the patient data. To verify the data in the blocks Proof of Stake (PoS) consensus protocol is employed. We propose Dragonfly Optimization based Blowfish Encryption algorithm (DO-BEA) that generates multiple keys for encrypting the data. The performance of the proposed system is evaluated and compared with the conventional approaches. The suggested approach has made it easier to store patient information safely and securely in the health-care system. In all circumstances, the information kept has been demonstrated to be reliable and unchanging, and it needs the consent of appropriate authorities. Healthcare becomes more safe, decentralized, automated, and affordable to everyone as a result.
Implementation of a Blockchain-based Smart Shopping System for Automated Bill Generation Using Smart Carts with Cryptographic Algorithms

On holidays and weekends, retail malls in metro areas have heavy foot traffic. Billing in the conventional manner, which entails employees standing in a line and scanning each customer’s purchase with a barcode scanner, is time-consuming. When there is a mistake in barcode scanners, the cashier may have to manually input the barcode number. As a consequence of this technique, clients are inconvenienced by lengthy lines at the billing counters. To overcome this issue, this chapter implemented a blockchain based smart shopping system. Here, smart carts are employed which performs the automated bill generation using the information from the Radio Frequency Identification (RFID) reader. The data from the smart carts are validated using the smart contracts and stored in the blockchain network for efficient bill generation. To avoid the data from being tampered, we have proposed Synchronous Discrete Twofish Encryption Algorithm (SDTEA), optimized using Genetically Modified Firefly Optimization Algorithm (GM-FOA). The bill is generated using the encrypted data and payment can be done after decryption of data. The simulation findings reveal that, by using this approach, a lot of time and man power can be saved. The proposed system is compared with conventional systems to prove its efficiency.
Infrared image enhancement technology based on human visual characteristics and adaptive side window bilateral filter

At present, the output image of infrared imaging system is high dynamic range image, which is difficult to display on traditional low dynamic range display device. And infrared images have the problems of concentrated gray distribution, small detail contrast and low contrast. In order to solve these problems and provide more details which make infrared images easy to observe, it is necessary to compress the dynamic range of infrared images and enhance the differences between details. In this paper, an adaptive side window bilateral filtering algorithm is studied. On the basis of edge preservation, the detail extraction performance and operation speed of the studied algorithm are improved. And an infrared image enhancement algorithm is constructed by combining the edge preserving filter with the salient characteristics of human vision. In this algorithm, adaptive side window bilateral filtering is used to separate the original image into base layer image and detail layer image firstly. In the base layer image, the adaptive dynamic range compression method based on Sigmoid function curve is adopted to improve the poor visual effect of processing results in some existing algorithms. In the detail layer image, visual saliency map is introduced to enhance the details and suppress noise amplification. The final result is obtained by weighted fusion of the processed base layer and detail layer. The simulation test of real scene infrared image have shown that the proposed algorithm in this paper can effectively enhance the infrared image, facilitate the visual perception of human eyes and has good robustness and stability.
Money and Finance

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
Poverty, Inequality, and Gender

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
International Trade

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
Geo-Human Interaction

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
Health

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
Geographical Economics and Development

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
Heterogeneous and Multinational Firms

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
Economic Development Today

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
Human Development

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.