Photo Selection Research Articles

Image moment extraction based aerial photo selection for UAV high-precision geolocation without GPS

Since GPS is susceptible to environmental interference or cannot be used in some specific situations, it is important to study the UAV geolocation under GPS-free condition. How to ensure that the aerial photos used for positioning have high accuracy is a pressing concern. The conventional approach relies on the number of matching feature points between aerial and satellite photos and verifying whether the aerial photo center projection falls within a designated area of the satellite photo. However, this method often yields suboptimal accuracy. This paper introduces a novel method for selecting aerial photos for geolocation based on an image moment extraction module. The image moment extraction module contains two parts: the relative error of the image invariant moment and the area relative error. The former is used to select the aerial photos with good performance in translation, rotation and scaling before and after projection, and the latter is adopted to reject aerial photos with excessive scaling before and after projection. Through experiments, we demonstrate the effectiveness and superiority of this approach. Results show that the image moment extraction module, when used for positioning with aerial photo center projection, significantly reduces the mean absolute error in UAV geolocation from 63.220 m to 9.454 m. The maximum error is reduced from 486.7 m to 47.194 m, with 70.96% of aerial photos suitable for positioning. This research is pivotal for achieving high-precision UAV geolocation in GPS-free environments.

"They Need to Feel Non-Judgmental": Results of Participatory Photovoice Research to Inform Lung Cancer Screening Imagery.

Effective communication and messaging strategies are crucial to raise awareness and support participants' efforts to adhere to lung cancer screening (LCS) guidelines. Health messages that incorporate images are processed more efficiently, and given the stigma surrounding lung cancer and cigarette smoking, emphasis must be placed on selecting imagery that is engaging to LCS-eligible individuals. This exploratory study aimed to identify person-centered themes surrounding LCS imagery. This qualitative study leveraged a modified photovoice approach and interviews to define descriptive themes about LCS imagery. Study participants eligible for annual LCS who had a CT scan within 12 months were asked to select three images and participate in a semi-structured interview about photo selection, likes, and dislikes. Participants were also asked their opinions about images from current LCS communications featuring matches, smoke, and cigarettes. Data were analyzed using an inductive thematic approach. Data saturation was reached after thirteen individuals completed the photovoice activity; each participant selected three pictures resulting in a total of 39 images representing LCS. Over half (54%) of images selected contained lungs and only 4 (10%) contained smoking-related elements. Five main themes emerged: 1) images should focus on good news and early detection; 2) people should be relatable; 3) pictures with lungs can dually support lung health or invoke fear; 4) opportunity for education or awareness; and 5) should not be judgmental and induce stigma. These findings suggest that LCS imagery should not contain negative or stigmatizing elements but instead be relatable and educational. This information can inform communication and messaging interventions and strategies for future LCS participation, awareness, and educational research.

Modeling Multiple Aesthetic Views for Series Photo Selection

Modeling Multiple Aesthetic Views for Series Photo Selection

Pembentukan Citra Diri dalam Media Sosial Instagram: Kajian pada Mahasiswa Ilmu Komunikasi Universitas Trunojoyo Madura

Instagram as a social media has become a major platform for individuals to build their self-image online. This research aims to explore and analyze strategies for forming the self-image of Communication Science students at Trunojoyo University, Madura on the social media Instagram. Qualitative research methods were used to interview participants from Communication Science students who actively use Instagram. The research results show that students use various strategies, including photo selection, captions, filters, and hashtags, to build the desired self-image. They also manage interactions with followers and respond to comments to strengthen their self-image. Additionally, findings suggest that social pressure, cultural norms, and peer influence play an important role in the formation of self-image on social media. This research provides in-depth insight into how social media, especially Instagram, influences the formation of Communication Science students' self-image, and its implications for self-concept and social interactions in a digital context. This study also provides a foundation for the development of social media literacy among college students and stimulates further discussion about the impact of social media on individual identity construction.

In Pursuit of Beauty: Aesthetic-Aware and Context-Adaptive Photo Selection in Crowdsensing

The pervasive view of the mobile crowd bridges various real-world scenes and people's perceptions with the gathering of distributed crowdsensing photos. To elaborate informative visuals for viewers, existing techniques introduce photo selection as an essential step in crowdsensing. Yet, the aesthetic preference of viewers, at the very heart of their experiences under various crowdsensing contexts (e.g., travel planning), is seldom considered and hardly guaranteed. We propose CrowdPicker, a novel photo selection framework with adaptive aesthetic awareness for crowdsensing. With the observations on aesthetic uncertainty and bias in different crowdsensing contexts, we exploit a joint effort of mobile crowdsourcing and domain adaptation to actively learn contextual knowledge for dynamically tailoring the aesthetic predictor. Concretely, an aesthetic utility measure is invented based on the probabilistic balance formalization to quantify the benefit of photos in improving the adaptation performance. We prove the NP-hardness of sampling the best-utility photos for crowdsourcing annotation and present a (1-1/e) approximate solution. Furthermore, a two-stage distillation-based adaptation architecture is designed based on fusing contextual and common aesthetic preferences. Extensive experiments on three datasets and four raw models demonstrate the performance superiority of CrowdPicker over four photo selection baselines and four typical sampling strategies. Cross-dataset evaluation illustrates the impacts of aesthetic bias on selection.

‘Fake’ Instagram use is associated with real differences in users' self-photo activities: An exploratory investigation considering body satisfaction

BackgroundCreating private spaces on social media (SM) for authentic self-presentation has rapidly gained popularity amongst young people. This pattern of use is particularly prevalent on Instagram in women under 25 as these users often report creating a second, low stakes account for authentic self-presentation, commonly referred to as a Finsta (a portmanteau of ‘Fake’ and ‘Instagram’). Previous research has associated Instagram use with body dissatisfaction in young women, but it remains unclear whether this association is applicable when considering different patterns of use. MethodThe present study investigates the association between self-photo activities (i.e., photo selection, investment, and manipulation) and body satisfaction in a sample of undergraduate female Instagram users (N = 224) with (n = 112) and without (n = 112) a Finsta. ResultsA series of analyses of covariance (ANCOVA) controlling for minutes on Instagram and age revealed that, when comparing their Finsta to their own main account and to the main account of users without a Finsta, Finsta users reported taking fewer photos of themselves, engaging in less photo editing, and feeling less invested in their posts. Furthermore, body satisfaction was differentially associated with self-photo activities in Finsta users and non-users. Specifically, body satisfaction was negatively associated with photo selection, investment, and editing in users without a Finsta only. ConclusionFinsta users do not show the same associations between body satisfaction and self-photo activities as Instagram users without a Finsta. The implications of these results, limitations of the present study, and suggestions for future research are discussed.

An Analysis of Subculture in Fan-made Products in China, Japan and Korea

With the development of idol culture in recent years, the fandom culture is getting more and more attention in the society. We found that the fan-made goods of the fandom culture have distinct design differences in China, Japan and South Korea. In order to find out the causes of these differences, we summarized relevant literatures, and compared several design cases in three aspects: background design, main character photo selection and color. The results of our study point to three reasons for the differences in design among the three countries: the different degree of development of the idol industry, the difference in the understanding of beauty and inherent concepts in traditional culture, and the different mainstream aesthetics of contemporary society

Empathic reactions to press photographs from the War in Ukraine: A Q-sort study

This study scrutinizes press photographs published during the first 6 weeks of the Russian War in Ukraine, beginning February 24th, 2022. Its objective is to shed light on the emotions evoked in Internet-savvy audiences. This empirical research aims to contribute to the understanding of emotional media effects that shape attitudes and actions of ordinary citizens. Main research questions are: What kind of empathic reactions are observed during the Q-sort study? Which visual patterns are relevant for which emotional evaluations and attributions? The assumption is that the evaluations and attributions of empathy are not random, but follow specific patterns. The empathic reactions are based on visual patterns which, in turn, influence the type of empathic reaction. The identification of specific categories for visual and emotional reaction patterns are arrived at in different methodological processes. Visual pattern categories were developed inductively, using the art history method of iconography-iconology to identify six distinct types of visual motifs in a final sample of 33 war photographs. The overarching categories for empathic reactions—empty empathy, vicarious traumatization and witnessing—were applied deductively, building on E. Ann Kaplan's pivotal distinctions. The main result of this research are three novel categories that combine visual patterns with empathic reaction patterns. The labels for these categories are a direct result of the Q-factorial analysis, interpreted through the lense of iconography-iconology. An exploratory nine-scale forced-choice Q-sort study (Nstimuli= 33) was implemented, followed by self-report interviews with a total of 25 participants [F= 16 (64%),M= 9 (36%),Mage= 26.4 years]. Results from this exploratory research include motivational statements on the meanings of war photography from semi-structured post-sort-interviews. The major result of this study are three types of visual patterns (“factors”) that govern distinct empathic reactions in participants: Factor 1 is “veiled empathy” with highest empathy being attributed to photos showing victims whose corpses or faces were veiled. Additional features of “veiled empathy” are a strong anti-politician bias and a heightened awareness of potential visual manipulation. Factor 2 is “mirrored empathy” with highest empathy attributions to photos displaying human suffering openly. Factor 3 focused on the context. It showed a proclivity for documentary style photography. This pattern ranked photos without clear contextualization lower in empathy than those photos displaying the fully contextualized setting. To the best of our knowledge, no study has tested empathic reactions to war photography empirically. In this respect, the study is novel, but also exploratory. Findings like the three patterns of visual empathy might be helpful for photo selection processes in journalism, for political decision-making, for the promotion of relief efforts, and for coping strategies in civil society to deal with the potentially numbing or traumatizing visual legacy of the War in Ukraine.

Recursive Multi-Relational Graph Convolutional Network for Automatic Photo Selection

Automatic Photo Selection (APS) is a fundamental and important task for further photo cropping and photo enhancement. As the images in a photo series normally have subtle differences, it remains challenging to surface the best photos among highly similar photos. In this work, we propose a Recursive Multi-Relational Graph Convolutional Network (RMGCN) for APS. Specifically, we explore and devise inner-relation and inter-relation graphs to learn informative representations in hierarchical manner. 1) Patch-aware Intra Graph Module (PIGM) captures visual and spatial relations between different patches to characterize the representations in an image. 2) Context-aware Inter Graph Module (CIGM) explicitly exploits mutual comparative relation between different images in a photo series. These two graphs are recursively refined each other by reasoning the graph representations. Then, our model aggregates the output of CIGM with multi-scale local features via the proposed Cross-domain Fusing Gate (CFG) to boost the discriminative ability. Besides, we formulate four companion objectives as soft constraints to improve convergence rate during training. Extensive experiments are conducted on photo-triage dataset, and superior results are reported on different metrics when comparing to the state-of-the-art methods. We also perform rigorous ablations and analysis to validate our approach.

Classification of News Texts by Categories Using Machine Learning Methods

In parallel with the advances in technology, digital journalism is preferred more than printed journalism day by day. Due to the fast and up-to-date sense of journalism provided by digital journalism and its ubiquitous accessibility features, it is read more by users. In addition to these advantages provided by digital journalism, it also has some difficulties compared to printed journalism. The stage of preparation and delivery of the news to the user requires more technological knowledge and equipment compared to printed journalism. The processes of title selection, text creation, photo selection and determination of the appropriate news category in the preparation phase of the news are designed to be both faster and user-friendly compared to printed publishing. The news created to be presented to the target audience may belong to one or more of different categories such as economy, politics, sports, technology, and health. The inclusion of the news in the appropriate category provides convenience in terms of reaching the right audience and archiving the news correctly. In this study, news texts were classified according to their categories based on the machine learning methods. In the study, news of five newspapers in three different categories were used. Bayesian classifier and decision tree methods were used to classify the news in the dataset including a total of 10.500 news. In the results of the study, it was observed that the Bayesian classifier classified the news more successfully according to their categories.

Pelatihan Jurnalistik Filantropi Islami Bagi Eksekutif Kantor Layanan Lazismu Se-kabupaten Jember

Community Service Program (PPM) is implemented to help increase the acquisition of donations through the payment of zakat, infaq, and shadaqah, at LAZISMU Jember Regency, through branding activities by utilizing various media, both online and social media. This Community Service Program aims to empower amilin officers from LAZISMU Jember, to be more creative and innovative in raising donations from muzaki or donors. This method of devotion is carried out by providing training in philanthropic journalism, ranging from human interest-based news writing techniques, interesting activity photo selection techniques, and publication techniques, by utilizing online media and various social media platforms. The target of this activity is the executives of Lazismu Service Office (KLL) in Jember Regency. So far, LAZISMU executives have acted in accordance with the program. Includes publication of activities through social media. However, the acquisition of ZIS funds raised has not been optimal. Therefore, more creative and innovative fundraising activities are needed, including through more massive publicity activities, to raise public awareness, especially Muslims donating, by issuing zakat, infaq, and shadaqah funds, which are paid through ammil institutions, including LAZISMU Jember.

Multiple Smile Detection Using Histogram of Oriented Gradient and Support Vector Machine Methods

The face or the front of the head consists of the eyes, nose and mouth. Each face has its uniqueness from the many human faces. The face is used to show happy and sad expressions and feelings. Smiling also includes self-expression from others. The analysis of facial expressions plays a key role in analyzing human emotions and behavior. Smile detection is a specialized task in facial expression analysis with a variety of potential applications such as photo selection, user experience analysis, smile payments, and patient monitoring. Conventional approaches often extract low-level face descriptors and smile detection based on strong binary classifiers. In this paper, we propose an effective Histogram of Oriented method supporting vector engines for smile detection. The experimental results show that our proposed network outperforms the current state of the method. The test results using the Histogram of Oriented Gradient and Support Vector Machine method for smile detection were 87% for a precision value of 88% and a recall value of 83% and accuracy. In the future, we want to exploit some of the latest effective designs. we will try to update our mouth model so we can support a bigger head turn and face size scale.

A Utility Model for Photo Selection in Mobile Crowdsensing

Existing mobile photo crowdsensing approaches focus on the participant-to-server photo pre-selection, i.e., reducing the photo redundancy from participants to a server. The server may still receive plenty of photos for a target area. Yet, another important problem is to select a proper photo subset of an area from the server to a requester. This is a challenging problem because the selected subset with a small size should attain both coverage on the PoIs - Points of Interest (i.e., photo coverage of the area) and quality on the views (i.e., view quality). In this paper, we propose a novel and generic server-to-requester photo selection approach even when there are neither photo shooting direction information nor reference photos. A utility model is designed to measure photo merits of coverage and quality by exploiting photos' spatial distribution and visual representativeness. We present two photo selection schemes, basic and PoI number-aware, to maximize the photo selection utility with multiple levels of granularity. Experimental results on real-world datasets show that our basic scheme outperforms the baselines by an average of 33% and 18.7% on photo coverage and view quality, respectively. Our PoI number-aware scheme can yield an additionally 44.8 percent improvement on the photo coverage performance.

Picture perfect? Gazing into girls’ health, physical activity, and nutrition through photovoice

ABSTRACT Background: Women face contradictions regarding their health: Pressure to be feminine, but also athletic; Criticism for being too sporty or muscular, but equally so for being perceived as lazy or overweight. These complexities are perpetuated through media and discourse. Purpose: Using a feminist post-structural approach and photovoice, this study explored health, physical activity, and nutrition in adolescent girls and young women. Methods: Photovoice enables reflection, promotes dialogue, and sparks change. The process involved conducting a workshop, collecting photos, and participatory analysis sessions, which engaged the participants (n = 7, ages 13–26) in photo selection, contextualization, and codifying. Results: This resulted in three themes: First, (Breaking) Stereotypes, in which participants identified gender norms, conflicts, and contradictions; Second, Emotional Safety, or the contexts in which girls and young women feel confident and comfortable; Finally, Being Outside in Nature emerged as significant. Each theme is supported by quotations and photographs. This work suggests being outside in nature provides important context for girls and young women to feel emotionally safe, such that they may engage in the complex navigation of competing discourses surrounding health.

Sentiment-based sub-event segmentation and key photo selection

The number of people collecting photos has surged owing to social media and cloud services in recent years. A typical approach to summarize a photo collection is dividing it into events and selecting key photos from each event. Despite the fact that a certain event comprises several sub-events, few studies have proposed sub-event segmentation. We propose the sentiment analysis-based photo summarization (SAPS) method, which automatically summarizes personal photo collections by utilizing metadata and visual sentiment features. For this purpose, we first cluster events using metadata of photos and then calculate the novelty scores to determine the sub-event boundaries. Next, we summarize the photo collections using a ranking algorithm that measures sentiment, emotion, and aesthetics. We evaluate the proposed method by applying it to the photo collections of six participants consisting of 5,480 photos in total. We observe that our sub-event segmentation based on sentiment features outperforms the existing baseline methods. Furthermore, the proposed method is also more effective in finding sub-event boundaries and key photos, because it focuses on detailed sentiment features instead of general content features.

An Edge Computing-Based Photo Crowdsourcing Framework for Real-Time 3D Reconstruction

Image-based three-dimensional (3D) reconstruction utilizes a set of photos to build 3D model and can be widely used in many emerging applications such as augmented reality (AR) and disaster recovery. Most of existing 3D reconstruction methods require a mobile user to walk around the target area and reconstruct objectives with a hand-held camera, which is inefficient and time-consuming. To meet the requirements of delay intensive and resource hungry applications in 5G, we propose an edge computing-based photo crowdsourcing (EC-PCS) framework in this paper. The main objective is to collect a set of representative photos from ubiquitous mobile and Internet of Things (IoT) devices at the network edge for real-time 3D model reconstruction, with network resource and monetary cost considerations. Specifically, we first propose a photo pricing mechanism by jointly considering their freshness, resolution and data size. Then, we design a novel photo selection scheme to dynamically select a set of photos with the required target coverage and the minimum monetary cost. We prove the NP-hardness of such problem, and develop an efficient greedy-based approximation algorithm to obtain a near-optimal solution. Moreover, an optimal network resource allocation scheme is presented, in order to minimize the maximum uploading delay of the selected photos to the edge server. Finally, a 3D reconstruction algorithm and a 3D model caching scheme are performed by the edge server in real time. Extensive experimental results based on real-world datasets demonstrate the superior performance of our EC-PCS system over the existing mechanisms.

Gender differences in competitiveness and narcissism as exhibited through pictures on Facebook

The purpose of the current study was to explore the influence of competitiveness on the photos that men and women choose to present of themselves on Facebook. Participants consisted of 236 undergraduate students. Participants completed competitiveness and narcissism scales. Participants allowed researchers to screen shot their most recent 10 Facebook photos, including their profile. Results indicated that competitive men were more likely to post athletic photos. Men lower in vanity were more likely to post attractive photos. Men and women higher in authority/entitlement were more likely to post sexual photos. Overall, the study supports the argument that both competitiveness and narcissism influence the photos that men and women choose to post on social media. In addition, competitiveness and narcissism predicted different types of photo selection.

Design and technological requirements for the production of the TV Media reports by 360 technology

The television report is one of the important templates in the satellite channels, through the delivery of information, details of events and the impressions of specialists to the recipient in a professional manner according to the standards and traditions of television work, which is completely different from other news sources and other templates. Correspondents compete to find different ideas, each according to his point of view and the way in which the information arrives, and the details of the event, whatever the political, cultural, sports. Television journalism in general suffers from a significant lack of attention among viewers. On average it can not keep the viewer's attention for more than forty seconds. But the intense competition between satellite TV on the one hand and between state television on the other makes it difficult to keep the viewer tight in front of the television screen. In order to keep the viewer in front of the screen as long as possible. This will only be achieved by working to provide as much accurate and new information as possible in an attractive and simple template that the viewer accepts. Most television reports, or directed to social media platforms, were very ordinary, sometimes similar, containing the same images and angles. But the BBC produced 360-degree video stories that brought viewers to the center of the event without angles or photo selection. BBC was not the only one. The use of these technologies is an opportunity for interactive journalistic experiences different from those used by the public in the past.This research aims to identify the design and technological requirements and the most important cameras used to produce 360-degree media reports. From Wagih Search: Search adopted in the course on the descriptive approach and analysis Almstkhaddh methods for the production of media reports produced a 360-degree technology, access to how to keep pace, especially in the world of photography and Internet technology for technological development.

Mobile photo recommendation system of continuous shots based on aesthetic ranking

Abstract Image aesthetics have been a popular topic in the recent years. The users can obtain aesthetic score of any image by using the computational approaches based on photography rules. However, most approaches consider the task as an off-line process because those methods usually require high computational complexity. On the other hand, mobile devices (tablet and smart phone) have become an indispensable tool in our daily life. Many users are more willing to take photos with them instead of digital cameras. Thus, developing practical camera applications (APPs) for mobile devices has high application potential. In this paper, respect to the issue of hardware computation limitation of mobile devices, we first design an instant photo aesthetics evaluation method. It adopts several simple and effective features to predict photo scores. The preliminary results conducted on benchmark datasets verify its performance and efficiency. Based on this achievement, we develop a continuous-shot photo recommendation system. It includes two steps: dominant photo selection performed in partially-decoded compression domain and instant photo aesthetics ranking. The system can automatically list the photos with higher scores, and help users to select desired ones. Crowd sourcing tests are employed to evaluate system performance, which show that our system is effective for instant aesthetic rating and photo recommendation. 1

Reassessing public opinion of captive cetacean attractions with a photo elicitation survey.

BackgroundCaptive cetacean attractions are growing in number globally, their operators citing entertainment, education, and conservation as benefits. Those for and against developing such attractions claim public support. Previous public opinion research, however, shows little consensus, partly due to the introduction of biases in study design that influence participants’ responses. Those involved in, or concerned with, developing and licensing these attractions need to better understand what drives the lack of consensus to take socially-acceptable decisions.MethodsWe reviewed previous research on public opinion of cetacean captivity, noting possible sources of bias. Survey question wording can be a major source of introduced bias, so we used an open-ended photo elicitation approach. We showed tourists in the Turks Caicos Islands (N = 292) images of a marine mammal park (MMP) killer whale show and a swim-with-the-dolphins (SWTD) attraction and asked for their qualitative comments on the potential development of each. They also indicated how likely they would be to visit each on a Likert scale.ResultsRespondents were generally against visiting MMP killer whale shows, with 60.9% not likely to visit. SWTD attractions were more popular; 60.3% were likely to visit. For SWTD, USA residents were more likely to visit; older respondents and those staying in all-inclusive resorts were less likely. Those staying in all-inclusive resorts were also less likely to visit MMP killer whale shows. The great majority of qualitative comments centred on either entertainment value or animal welfare concerns. There were very few, if any, comments on the education or conservation value of these attractions.DiscussionOur findings contradict several previous studies on public opinion of captive cetaceans that did not use photo elicitation. The support shown for MMP killer whale shows in this survey was well below that claimed by studies conducted on behalf of captive cetacean attraction operators. Opposition to SWTD was also noticeably lower than that found in surveys conducted with wild cetacean tourism participants. This difference can likely be attributed to the different survey populations and settings, but this variation is also very likely attributable to researcher-introduced bias. While photo selection can introduce bias, photo elicitation reduces reliance on pre-scripted questions and responses, and seems to effectively reduce other forms of bias. Allowing open-ended responses, where participants responded to an image, seems to have given a more representative understanding of what is at the forefront of the public’s mind than closed questioning. These conclusions, among others made in this study, suggest that development decisions for captive cetacean attractions are being made on imprecise data. Going forward, data collected via responder-led, open-ended, bias-minimising approaches should at least be considered when informing such decisions.