Effects of display technique, background complexity, and target size on visual performance evaluation–A case study using the “Spot The Difference” game

A large amount of classic and contemporary vision studies require subjects to fixate a target. Target fixation serves as a normalizing factor across studies, promoting the field’s ability to compare and contrast experiments. Yet, fixation target parameters, including luminance, contrast, size, shape and color, vary across studies, potentially affecting the interpretation of results. Previous research on the effects of fixation target size and luminance on the control of fixation position rendered conflicting results, and no study has examined the effects of fixation target characteristics on square-wave jerks, the most common type of saccadic intrusion. Here we set out to determine the effects of fixation target size and luminance on the characteristics of microsaccades and square-wave jerks, over a large range of stimulus parameters. Human subjects fixated a circular target with varying luminance and size while we recorded their eye movements with an infrared video tracker (EyeLink 1000, SR Research). We detected microsaccades and SWJs automatically with objective algorithms developed previously. Microsaccade rates decreased linearly and microsaccade magnitudes increased linearly with target size. The percent of microsaccades forming part of SWJs decreased, and the time from the end of the initial SWJ saccade to the beginning of the second SWJ saccade (SWJ inter-saccadic interval; ISI) increased with target size. The microsaccadic preference for horizontal direction also decreased moderately with target size . Target luminance did not affect significantly microsaccades or SWJs, however. In the absence of a fixation target, microsaccades became scarcer and larger, while SWJ prevalence decreased and SWJ ISIs increased. Thus, the choice of fixation target can affect experimental outcomes, especially in human factors and in visual and oculomotor studies. These results have implications for previous and future research conducted under fixation conditions, and should encourage forthcoming studies to report the size of fixation targets to aid the interpretation and replication of their results.

INTRODUCTIONLarge movements in the visual field trigger stereotypic eye movements in vertebrates. This optokinetic response (OKR) is robust in zebrafish (Danio rerio) larvae older than 4 days post-fertilization (dpf), and is hence ideally suited for use in the evaluation of visual performance after genetic manipulations. This protocol describes a simple method by which a computer-generated visual stimulus is projected onto a screen and watched by immobilized larvae. The resulting eye movements are recorded and evaluated automatically, using a digital video camera and appropriate computer software. Depending on the sophistication of the software used, the evaluation can be performed in real time during the recording session, or by analyzing the recorded movie files off-line.

PurposeThe more precise decision map is important to generate better-fused image. Guided filter can preserve edge information effectively. The purpose of his study is to use guided filter to form the precise decision map and highly informatively fused image.Design/methodology/approachThe dual tree complex wavelet transform is adopted to decompose the source images into high frequency and low frequency coefficients. Sum of modified Laplacian method is introduced as the focus metric in dual tree complex wavelet coefficients. The guided filter is guided by the dual tree complex wavelet coefficient when the sum of modified Laplacian is used as the input image. The output image of guided filter is used to produce the decision map to fuse dual tree complex wavelet coefficient of source images.FindingsThe sum of modified Laplacian of dual tree complex wavelet coefficient can be used as the guided image in guided filter to generate better decision map. Comparison with the other state-of-the-art methods illustrates that the proposed approach is more effective in fusing the multifocus images both visual performance and objective evaluation.Originality/valueThe sum of modified Laplacian of dual tree complex wavelet coefficient is introduced to be used as the guided image in guided filter to generate better decision map. This method is fast and effect to fuse the source images. Comparison with the other state-of-the-art methods illustrates that the proposed approach is more effective in fusing the multifocus images both visual performance and objective evaluation.

In large shopping malls, shoppers often require assistance with wayfinding. Intelligent shopping guide terminals are increasingly being used for this purpose, and their interface usability plays a crucial role in influencing both wayfinding visual search performance and the overall shopping experience. This study investigates the effects of map visual presentations and landmark description locations in virtual environments on users’ wayfinding visual search performance and subjective evaluations using intelligent shopping guide terminals. A 2x3 between subject design was employed to examine how different virtual map types (2D and 3D) and landmark description locations (on, within, or below the map) affect task performance and subjective evaluations. A total of 60 participants were selected via purposive sampling and asked to complete five wayfinding tasks. Task completion times were recorded, and data were collected using the System Usability Scale (SUS), a 7-point Likert scale for subjective evaluation, and semi-structured interviews. The key findings are as follows: (1) Landmark descriptions on or below the map led to better wayfinding visual search performance than those within the map; (2) Users demonstrated superior wayfinding visual search performance with 3D maps compared to 2D maps; (3) When landmarks were placed on or below the map, 3D maps outperformed 2D maps in task performance, attractiveness, and information clarity. However, the reverse was true when landmarks were placed within the map, (4) Landmark descriptions within the map generated higher physical demand, with no significant difference between descriptions on or below the map. (5) Overall, subjective evaluations and SUS scores indicated a clear preference for landmark descriptions placed on or below the map. These findings contribute to improving wayfinding visual search performance in shopping malls and offer valuable insights for enhancing user interface design in intelligent shopping guide terminals, ultimately leading to better user experiences.

To evaluate the rangefinding and light sensing capabilities of a novel wearable sensor, the Visual Environment Evaluation Tool (VEET) developed for myopia research. The VEET 1.0 (Meta, LLC) is a temple-integrated system mounted on a spectacle frame. Both the left and right temples house four sensors each, angled straight ahead and 20° downward/4° nasal, respectively. For validation, VEET-mounted spectacles were placed on a mannequin head. An infrared camera was used to capture the spatial characteristics of the rangefinding beam. Distance measurements were collected against a wall for 5-400 cm. The accuracy of distance measurements for different target types, sizes and tilt was assessed. Ambient illumination was captured in different indoor and outdoor settings and compared to a lux meter. All devices (N = 20) were capable of capturing distances for the full range evaluated, 5-400 cm, against a wall. There was a strong relationship between the actual and measured distances, with a slope of 1.01 ± 0.003 and 0.95 ± 0.007, for the left and right temples, respectively. Distance measurements were repeatable across different target types, including paper and tablet. Mean beam diameter of five tested devices was 52.2° ± 7.5°. The VEET effectively measured distances across different target sizes, ranging from 2 × 2 cm and larger and target tilt ±60°. Illumination measurements across different indoor and outdoor settings demonstrated a strong linear relationship with lux meter readings (R2 = 0.99 and 0.78 for the left and right temples, respectively), effectively distinguishing indoor (<1000 lux) and outdoor (≥1000 lux) illumination levels. The VEET provides accurate quantification of real-time distances across different target types and sizes and is capable of effectively distinguishing indoor and outdoor illumination levels. The VEET will be valuable in studies evaluating risk factors for myopia to gaina better understanding of the role of near work and light exposure.

According to the characteristics of the low frequency and the high frequency coefficients of wavelet decomposition, a new adaptive image fusion method based on local statistical feature of wavelet coefficients is presented in this paper. For the low frequency coefficients, taking the local energy of the image as a criterion, an adaptive fusion rule of combining weighted average with selection is used to obtain the approximate coefficients. For the high frequency coefficients, on the basis of local variance and covariance, an adaptive weighted average method is used to obtain the detail coefficients. The image entropy and the cross entropy can be computed to evaluate the performance of the proposed method and other wavelet-based image fusion methods. Experiments show that the proposed method can achieve better effect than other methods in the human visual perception and objective performance evaluation.

Medical image segmentation has long been a compelling and fundamental problem in the realm of neuroscience. This is an extremely challenging task due to the intensely interfering irrelevant background information to segment the target. State-of-the-art methods fail to consider simultaneously addressing both long-range and short-range dependencies, and commonly emphasize the semantic information characterization capability while ignoring the geometric detail information implied in the shallow feature maps resulting in the dropping of crucial features. To tackle the above problem, we propose a Global-Local representation learning net for medical image segmentation, namely GL-Segnet. In the Feature encoder, we utilize the Multi-Scale Convolution (MSC) and Multi-Scale Pooling (MSP) modules to encode the global semantic representation information at the shallow level of the network, and multi-scale feature fusion operations are applied to enrich local geometric detail information in a cross-level manner. Beyond that, we adopt a global semantic feature extraction module to perform filtering of irrelevant background information. In Attention-enhancing Decoder, we use the Attention-based feature decoding module to refine the multi-scale fused feature information, which provides effective cues for attention decoding. We exploit the structural similarity between images and the edge gradient information to propose a hybrid loss to improve the segmentation accuracy of the model. Extensive experiments on medical image segmentation from Glas, ISIC, Brain Tumors and SIIM-ACR demonstrated that our GL-Segnet is superior to existing state-of-art methods in subjective visual performance and objective evaluation.

Background Multifocal lens has become popular in cataract surgery. Short-term outcome after AcrySof ReSTOR Lens implantation had been reported by many studies, but long-term visual performance and the effect of posterior capsular opacification (PCO) on visual performance need further investigation. Methods This retrospective study involved 54 eyes from 41 cataract patients implanted with ReSTOR lens, with a follow-up period of 12 to 31 months. Manifest refraction spherical equivalence (MRSE), monocular uncorrected and best-corrected distance visual acuity, uncorrected and distance-corrected near and intermediate visual acuity, contrast sensitivity were assessed. The effect of PCO on visual performance was evaluated by comparing visual parameters between pre and post-capsulotomy. Results Uncorrected distance visual acuity of eyes with MRSE within ±0.5 diopter (D) was better than those with MRSE greater than ±0.5 D (P &lt;0.05). Uncorrected distance and near visual acuity (LogMAR) was 0.10 and 0.17 respectively. Best corrected distance visual acuity and best distance-corrected near visual acuity (LogMAR) was 0.00 and 0.16, a significant improvement was noted after correction (P=0.000, P=0.001, respectively). Contrast sensitivity logarithm was comparable with the normal value at difference spatial frequencies except at 12 cpd. In 5 eyes with mild PCO, post-capsulotomy visual parameters were better than pre-capsulotomy (P &lt;0.05). Conclusion ReSTOR lens provides a good long-term distance and near vision, functional intermediate vision and contrast sensitivity. Mild PCO significantly affects visual performance and needs early intervention.

The content-based image retrieval (CBIR) has been an active research field for which several feature extraction, classification and retrieval techniques have been proposed up to date. However, when the database size grows larger, it is a common fact that the overall retrieval performance significantly deteriorates. In this paper, we propose collective network of (evolutionary) binary classifiers (CNBC) framework to achieve a high retrieval performance even though the training (ground truth) data may not be entirely present from the beginning and thus the system can only be trained incrementally. The CNBC framework basically adopts a “Divide and Conquer” type approach by allocating several networks of binary classifiers (NBCs) to discriminate each class and performs evolutionary search to find the optimal binary classifier (BC) in each NBC. In such an evolution session, the CNBC body can further dynamically adapt itself with each new incoming class/feature set without a full-scale re-training or re-configuration. Both visual and numerical performance evaluations of the proposed framework over benchmark image databases demonstrate its scalability; and a significant performance improvement is achieved over traditional retrieval techniques.

Peripheral (out-to-the-side) vision is important for general mobility and tasks such as driving. This study evaluated appropriateness of testing methods used to measure peripheral optics and visual performance. Peripheral optics measurements depended on the instrument used to measure them. The choice of either head or eye movements to set up peripheral optics measurements was not critical, even when contact lenses were worn. The nature of targets, in terms of size and abrupt or gradual loss of contrast near the edge, affected peripheral detection. To measure peripheral contrast detection accurately in the presence of blur, fine spatial frequency sampling was required.

Inverse synthetic aperture radar (ISAR) imaging is typically useful when there is a need to classify, recognize, or identify a moving target of interest. In fact, an ISAR image highlights two-dimensional (2-D) geometric features of a target, which can provide indications of target's type, size, and other salient information. Such information can be then used for target classification, recognition, and identification. In this chapter, we will provide five case studies on applications of ISAR imaging. Such case studies are chosen to diversify the type of application and to give additional indications about how to interpret ISAR images. Specifically, in the first case study (Section 12.1), we show an example of ground-based ISAR images of a noncooperative sailing ship. The ISAR techniques used to form the ISAR images are the range-Doppler (Chapter 3) and the ICBA (Chapter 5) techniques. Different time windows are chosen to show the effects of the coherent processing interval (CPI) length on the ISAR image. Since the radar is ground based, this represents a case where the ISAR image is formed by exploiting only the sea surface induced target's motions. The second case study (Section 12.2) refers to a scenario where the radar is carried by an aircraft and the target is a ship at sea. In this case, both the target and the platform motions concur to the ISAR image formation. Also in this case, the range-Doppler and ICBA are used to form the ISAR image sequence. The third case study (Section 12.3) concerns dual ground-based/satellite ISAR imaging of a noncooperative sailing ship. In this experiment two radars are used to image a sailing ship at the same time. Two techniques are here used to form the ISAR images: a refocus technique (see Chapter 8) to form the satellite ISAR image; and a range-Doppler with ICBA to form the ground-based ISAR image. In this case study, we show how a dual system is able to form ISAR images of the same target with different target's views and projections. This is a simple case of multiple-perspective ISAR images, which may be looked at as a way to improve a target's classification and recognition [1]. The fourth case study (Section 12.4) shows ISAR images of four aircrafts obtained by processing data acquired with a ground-base radar. This case study may be regarded as the classic ISAR imaging example. Four different airplanes have been selected to show how their characteristics are mapped onto ISAR images. Such characteristics can then be used by classifiers for recognition purposes.

This study investigated the effects of the target size and movement distance on user performance and workload in a virtual reality (VR) environment. In a repeated-measures laboratory study, 36 participants (18 male and 18 female) performed the drag-and-drop task as a standard human–computer interaction (HCI) task with different target sizes (1, 1.5, 2, 2.5, and 3 cm) and movement distances (5, 9, 13, 17, and 20 cm). Task completion time (TCT), error rate, and movement time (MT) were measured as performance indices, whereas physical load and effort were assessed as workload indices. The results demonstrated that the target size and movement distance significantly affected all performance measures and workload indices. Large target sizes produced better performance and lower workloads; however, large movement distances decreased performance and increased workload. However, sex had no significant effect on the performance or workload during the drag-and-drop tasks. The best target sizes were 2.5 and 3 cm, and the worst size was 1 cm. The best movement distances were 5 and 9 cm, and the worst distance was 20 cm. The results of this study can provide useful reference information for developing VR technology based on human factors and demonstrate that additional basic research is required to reflect the distinctive features of VR in the future.

The last three decades have witnessed significant advances in psychotherapy. Numerous scholarly articles and books have been devoted to pertinent topics in the field, making it difficult for the practicing clinician to keep up with this rapidly growing area. The purpose of this article is to provide some guidelines on how to evaluate the empirical literature in psychotherapy and then to explore three key areas: evidence-based psychotherapies for patients with psychiatric disorders, individual variables that predict differential outcome to treatment, and the therapeutic alliance. Finally, two case examples will be presented to illustrate how knowledge of the empirical literature can facilitate an evidence-based approach to the daily practice of psychotherapy in general psychiatry.

Objective: This study sought to investigate whether the size of the target used in the horizontal vHIT has an effect on the saccade profile of healthy subjects, and to expand upon previous work linking age to the existence of small vHIT saccades.Methods: Forty eight participants were recruited between 18 and 77 years of age, with no history of vestibular, oculomotor or neurological conditions and a visual acuity of at least 0.3 LogMAR. Participants underwent four consecutive horizontal vHIT trials using the standard target size and three smaller targets. VOR gain and metrics for saccadic incidence, peak eye velocity and latency were then extracted from results.Results: Target size was a statistically significant influence on saccade metrics. As target size increased, saccadic incidence decreased while peak eye velocity and latency increased. However, a potential order effect was also discovered, and once this was corrected for the remaining effect of target size was small and is likely clinically insignificant. The effect of age was much stronger than target size; increasing age was strongly positively correlated with saccadic incidence and showed a medium size correlation with peak velocity, though not with saccadic latency.Conclusion: While this study suggests that target size may have a statistically significant impact on the vHIT saccade profile of normal subjects, age has a greater influence on the incidence and size of small vHIT saccades.

The effects of target size and error rate on the cognitive demand and stress during augmented reality interactions