Visual Target Research Articles

Your dermatology office visit: The effects of target visibility, target-distractor similarity, satisfaction of search, and time pressure on a visual search for cancerous moles

Your dermatology office visit: The effects of target visibility, target-distractor similarity, satisfaction of search, and time pressure on a visual search for cancerous moles

Kinematic Properties of Haptic-Free Reach-to-Grasp Movements in Virtual Reality: A Comparison with Natural Prehension in Real Spaces and Pantomimed Ones

Many researchers are interested in how the kinematics of reach-to-grasp movements in virtual reality (VR), which involve the vergence–accommodation conflict, differ from real space. The present study, conducted in VR, verified the effect of a discrepancy between visual and haptic target size and found that terminal haptic feedback is weighted more heavily than visual information, as is the case in real space. Furthermore, we investigated how the presence or absence of terminal haptic feedback modulates performance in VR by comparing prehension with or without terminal haptic feedback in VR, closed-loop natural grasping in real space, and pantomimed prehension with the eyes closed. Our results suggested that the contribution of a visual image to grip aperture adjustment is quite marginal in situations where terminal haptic feedback is unavailable, and that the performance in VR without haptic feedback is highly correlated with performances driven by fully internal representations (i.e., pantomimed movements).

Research on Lightweight Method of Insulator Target Detection Based on Improved SSD.

Aiming at the problems of a large volume, slow processing speed, and difficult deployment in the edge terminal, this paper proposes a lightweight insulator detection algorithm based on an improved SSD. Firstly, the original feature extraction network VGG-16 is replaced by a lightweight Ghost Module network to initially achieve the lightweight model. A Feature Pyramid structure and Feature Pyramid Network (FPN+PAN) are integrated into the Neck part and a Simplified Spatial Pyramid Pooling Fast (SimSPPF) module is introduced to realize the integration of local features and global features. Secondly, multiple Spatial and Channel Squeeze-and-Excitation (scSE) attention mechanisms are introduced in the Neck part to make the model pay more attention to the channels containing important feature information. The original six detection heads are reduced to four to improve the inference speed of the network. In order to improve the recognition performance of occluded and overlapping targets, DIoU-NMS was used to replace the original non-maximum suppression (NMS). Furthermore, the channel pruning strategy is used to reduce the unimportant weight matrix of the model, and the knowledge distillation strategy is used to fine-adjust the network model after pruning, so as to ensure the detection accuracy. The experimental results show that the parameter number of the proposed model is reduced from 26.15 M to 0.61 M, the computational load is reduced from 118.95 G to 1.49 G, and the mAP is increased from 96.8% to 98%. Compared with other models, the proposed model not only guarantees the detection accuracy of the algorithm, but also greatly reduces the model volume, which provides support for the realization of visible light insulator target detection based on edge intelligence.

High-frequency SSVEP-BCI system for detecting intermodulation frequency components using task-discriminant component analysis

Recently, steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has significantly progressed and is moving from the laboratory to practical application. However, the system performance and comfort of SSVEP-BCIs still need to be improved. In this study, five flicker frequencies (i.e., 30–34 Hz with an interval of 1 Hz) and eight scaling frequencies (i.e., 0.4–1.8 Hz with an interval of 0.2 Hz) were adopted to jointly encode forty visual stimulus targets using evoked intermodulation (IM) frequency components. Both luminance and shape changes are implemented by sinusoidal sampling stimulus coding methods. High-frequency flicker frequencies and green visual stimuli were chosen to improve the comfort of the proposed system. An extended version of a training algorithm named task-discriminant component analysis (TDCA) was proposed to detect the IM components of SSVEP signals. The average recognition accuracy of eleven subjects is 96.82 ± 0.01 % in the offline experiments for a data length of 5 s. Online validation experiments was constructed from the optimized parameters of offline analysis, and the average accuracy and ITR were 94.37 ± 1.17 % and 113.47 ± 2.60 bits/min, respectively. Furthermore, ten subjects who participated in the validation part also completed the online free-spell task successfully. These results showed that it is feasible to expand the number of stimulus targets by using IM frequency components of SSVEP signals for target coding, and that the system performance is superior.

Efficient Highlighting of Visual Targets in Complex Natural Scenes

Guided visual search is a common theme in HF applications. In this project we use large-scale databases of wildlife camera-trap imagery as a testbed for optimization of target highlighting. MegaDetector, a generic animal detection deep machine learning model, provides bounding boxes for potential targets within an image. In some cases, human observers are necessary to confirm or further classify the detections. Outlining the bounding box can direct human attention to the target AOI to improve observers’ classification speed and accuracy. However, this outline introduces visual clutter and crowding at the AOI boundary. In a first empirical study we investigate the use of padding to mitigate the effects of local clutter and compared different methods of visual highlighting (colored outline vs. blur outside of AOI). We found support for using padding to improve performance when animals were hard to see. Both colored outlines and blur were effective at directing observers’ attention.

Optimality of multisensory integration while compensating for uncertain visual target information with artificial vibrotactile cues during reach planning

BackgroundPlanning and executing movements requires the integration of different sensory modalities, such as vision and proprioception. However, neurological diseases like stroke can lead to full or partial loss of proprioception, resulting in impaired movements. Recent advances focused on providing additional sensory feedback to patients to compensate for the sensory loss, proving vibrotactile stimulation to be a viable option as it is inexpensive and easy to implement. Here, we test how such vibrotactile information can be integrated with visual signals to estimate the spatial location of a reach target.MethodsWe used a center-out reach paradigm with 31 healthy human participants to investigate how artificial vibrotactile stimulation can be integrated with visual-spatial cues indicating target location. Specifically, we provided multisite vibrotactile stimulation to the moving dominant arm using eccentric rotating mass (ERM) motors. As the integration of inputs across multiple sensory modalities becomes especially relevant when one of them is uncertain, we additionally modulated the reliability of visual cues. We then compared the weighing of vibrotactile and visual inputs as a function of visual uncertainty to predictions from the maximum likelihood estimation (MLE) framework to decide if participants achieve quasi-optimal integration.ResultsOur results show that participants could estimate target locations based on vibrotactile instructions. After short training, combined visual and vibrotactile cues led to higher hit rates and reduced reach errors when visual cues were uncertain. Additionally, we observed lower reaction times in trials with low visual uncertainty when vibrotactile stimulation was present. Using MLE predictions, we found that integration of vibrotactile and visual cues followed optimal integration when vibrotactile cues required the detection of one or two active motors. However, if estimating the location of a target required discriminating the intensities of two cues, integration violated MLE predictions.ConclusionWe conclude that participants can quickly learn to integrate visual and artificial vibrotactile information. Therefore, using additional vibrotactile stimulation may serve as a promising way to improve rehabilitation or the control of prosthetic devices by patients suffering loss of proprioception.

The phase coherence of cortical oscillations predicts dynamic changes in perceived visibility.

The phase synchronization of brain oscillations plays an important role in visual processing, perceptual awareness, and performance. Yet, the cortical mechanisms underlying modulatory effects of post-stimulus phase coherence and frequency-specific oscillations associated with different aspects of vision are still subject to debate. In this study, we aimed to identify the post-stimulus phase coherence of cortical oscillations associated with perceived visibility and contour discrimination. We analyzed electroencephalogram data from two masking experiments where target visibility was manipulated by the contrast ratio or polarity of the mask under various onset timing conditions (stimulus onset asynchronies, SOAs). The behavioral results indicated an SOA-dependent suppression of target visibility due to masking. The time-frequency analyses revealed significant modulations of phase coherence over occipital and parieto-occipital regions. We particularly identified modulations of phase coherence in the (i) 2-5Hz frequency range, which may reflect feedforward-mediated contour detection and sustained visibility; and (ii) 10-25Hz frequency range, which may be associated with suppressed visibility through inhibitory interactions between and within synchronized neural pathways. Taken together, our findings provide evidence that oscillatory phase alignments, not only in the pre-stimulus but also in the post-stimulus window, play a crucial role in shaping perceived visibility and dynamic vision.

Factors contributing to transient-induced fading: Examining the impact of luminance contrasts and subjective contours.

Transient-induced fading is a phenomenon where a peripheral target perceptually fades when a surrounding object is flashed. It has been suggested that the transient-induced fading could be affected not only by the lower-level factors such as the luminance contrast change, but also by the higher-level factors such as Gestalt grouping by similarity. In the present study, Experiment 1 investigated whether the perceptual fading of a visual target could be strongly induced when a ring area surrounding the target with high luminance contrast disappeared rather than appeared. Experiment 2 examined the effect of the (dis)appearance of a higher-level object (Kanizsa-type subjective contour) on the fading perception. Experiment 3 further investigated whether the rating of the perceived effortlessness of a subjective contour could be positively correlated with the fading duration of the target. Our results revealed that perceptual fading was mainly induced by the disappearance of fan areas inside black disks producing a subjective contour surrounding the target. Disappearance of a perceptual object at the representation level does not trigger the transient-induced fading even if a higher-level factor (e.g., grouping by similarity) affects the fading objects.

Pre-stimulus EEG phase coherence predicts visual target detection failures in schizophrenia: A pilot study

Impaired visual target detection is a common finding in schizophrenia that is linked to poor functional outcomes. However, the neural mechanisms that contribute to this deficit remain unclear. Recent research in healthy samples has identified relationships between the phase of pre-stimulus electroencephalographic (EEG) activity in the alpha band (8-12 Hz) or theta band (4-7 Hz) and the likelihood of visual target detection with and without attentional cueing, but these effects have not yet been explored in schizophrenia. We performed a study to investigate such effects in schizophrenia (n = 19) and healthy participants (n = 14), using a visual target detection task with attentional cues. We found significant relationships between pre-stimulus EEG phase properties and visual target detection in both groups, but also clear differences in the effects as a function of frequency, group, and attentional cueing. Alpha-band phase effects were relatively uniform across groups and conditions. By contrast, theta-band phase effects showed differences by group and attentional condition which could be consistent with attentional hyperfocusing in the schizophrenia group. Thus, our results elucidate a novel neural mechanism that may help to explain known impairments affecting both visual target detection and attention in schizophrenia.

Task difficulty of visually guided gait modifications involves differences in central drive to spinal motor neurons.

Walking in natural environments requires visually guided modifications, which can be more challenging when involving sideways steps rather than longer steps. This exploratory study investigated whether these two types of modifications involve different changes in the central drive to spinal motor neurons of leg muscles. Fifteen adults [age: 36 ± 6 (SD) years] walked on a treadmill (4 km/h) while observing a screen displaying the real-time position of their toes. At the beginning of the swing phase, a visual target appeared in front (forward) or medial-lateral (sideways) of the ground contact in random step cycles (approximately every third step). We measured three-dimensional kinematics and electromyographic activity from leg muscles bilaterally. Intermuscular coherence was calculated in the alpha (5-15 Hz), beta (15-30 Hz), and gamma bands (30-45 Hz) approximately 230 ms before and after ground contact in control and target steps. Results showed that adjustments toward sideways targets were associated with significantly higher error, lower foot lift, and higher cocontraction between antagonist ankle muscles. Movements toward sideways targets were associated with larger beta-band soleus (SOL): medial gastrocnemius (MG) coherence and a more narrow and larger peak of synchronization in the cumulant density before ground contact. In contrast, movements toward forward targets showed no significant differences in coherence or synchronization compared with control steps. Larger SOL:MG beta-band coherence and short-term synchronization were observed during sideways, but not forward, gait modifications. This suggests that visually guided gait modifications may involve differences in the central drive to spinal ankle motor neurons dependent on the level of task difficulty.NEW & NOTEWORTHY This exploratory study suggests a specific and temporally restricted increase of central (likely corticospinal) drive to ankle muscles in relation to visually guided gait modifications. The findings indicate that a high level of visual attention to control the position of the ankle joint precisely before ground contact may involve increased central drive to ankle muscles. These findings are important for understanding the neural mechanisms underlying visually guided gait and may help develop rehabilitation interventions.

Effect of luminance of head-up displays on recognition of visual objects on roads

ObjectiveThe purpose of this study is to investigate the effect of visual obstruction when a head-up display (HUD) is presented in front of a driver's field of view. BackgroundThe use of HUDs is expected to increase due to advances in augmented reality (AR) technology. A conventional HUD is displayed at a relatively low position in relation to the driver's viewpoint and has little effect on their front view. However, while an HUD, such as the AR-HUD, is presented in front of the driver's field of vision and helps them in presenting ADAS information, there is a concern that this display may obscure visual objects on the road from the driver's field of vision. MethodAn experiment using a mockup consisting of a HUD and a driver's seat was conducted with 28 participants. A passenger car, motorcycle, and crossing pedestrian were presented as visual objects on a 65-in monitor behind the image of the HUD. Participants were asked questions under different conditions with changes in the HUD luminance and asked to correctly answer questions regarding changes in the inter-vehicle distance and the existence of visual objects on the road. The number of correct answers provided by the participants was recorded. ResultsThe experimental results revealed that the HUD had an effect under the twilight condition wherein the background luminance was low. Furthermore, analyzing the number of correct answers for each visual target revealed that the HUD had an effect under conditions wherein the size of the visual object was small. ConclusionIt was experimentally derived that the luminance ratio Rluminance = 1.1 was the threshold value that affected the recognition of the visual object in the background when the HUD was presented in front of the driver's field of view. ImplicationThe threshold value of the luminance ratio Rluminance obtained in this study can be considered when deciding how to properly display the HUD in front of the driver's field of view.

Developmental Changes in How Head Orientation Structures Infants' Visual Attention.

Most studies of developing visual attention are conducted using screen-based tasks in which infants move their eyes to select where to look. However, real-world visual exploration entails active movements of both eyes and head to bring relevant areas in view. Thus, relatively little is known about how infants coordinate their eyes and heads to structure their visual experiences. Infants were tested every 3 months from 9 to 24 months while they played with their caregiver and three toys while sitting in a highchair at a table. Infants wore a head-mounted eye tracker that measured eye movement toward each of the visual targets (caregiver's face and toys) and how targets were oriented within the head-centered field of view (FOV). With age, infants increasingly aligned novel toys in the center of their head-centered FOV at the expense of their caregiver's face. Both faces and toys were better centered in view during longer looking events, suggesting that infants of all ages aligned their eyes and head to sustain attention. The bias in infants' head-centered FOV could not be accounted for by manual action: Held toys were more poorly centered compared with non-held toys. We discuss developmental factors-attentional, motoric, cognitive, and social-that may explain why infants increasingly adopted biased viewpoints with age.

Efficacy study of hyperbaric oxygen therapy for the treatment of central retinal artery occlusion: a systematic review

Central Retinal Artery Occlusion (CRAO) is a rare ophthalmology emergency caused by central retinal artery embolism. Many CRAO management strategies exist. However, no treatment has consistently improved visual outcomes following CRAO. These medicines have many negative effects and unclear efficacy. HBOT has been considered for CRAO management. HBOT may minimize ischemia damage between CRAO and retinal artery recanalization, which normally occurs within 72 hours.9 There is continuous disagreement about whether this treatment procedure achieves the desired visual target. The method use is PRISMA principles were followed for a systematic review. This systematic review examines HBOT's efficacy in CRAO. The search terms were “Hyperbaric Oxygen Therapy” (“HBOT”) and “Central Retinal Artery Occlusion” (“CRAO”). The 5 investigations were primarily cohort retrospective. Four studies found no link between onset-to-HBOT time and visual outcome, two found no correlation between HBOT session and VA improvement, and three found no correlation between first therapy before HBOT and VA improvement. All said this therapy produced side effects. The conclusion is in this study is more investigations showed no significant link between onset-to-HBOT time, initial treatment before HBOT, and VA improvement. HBOT can produce barotrauma, ear pain, tympanic membrane rupture, and central nervous system oxygen poisoning seizures, so these must be considered.

Visual object detection system based on augmented reality and steady-state visual evoked potential

This study investigates a brain-computer interface (BCI) system based on an augmented reality (AR) environment and steady-state visual evoked potentials (SSVEP). The system is designed to facilitate the selection of real-world objects through visual gaze in real-life scenarios. By integrating object detection technology and AR technology, the system augmented real objects with visual enhancements, providing users with visual stimuli that induced corresponding brain signals. SSVEP technology was then utilized to interpret these brain signals and identify the objects that users focused on. Additionally, an adaptive dynamic time-window-based filter bank canonical correlation analysis was employed to rapidly parse the subjects' brain signals. Experimental results indicated that the system could effectively recognize SSVEP signals, achieving an average accuracy rate of 90.6% in visual target identification. This system extends the application of SSVEP signals to real-life scenarios, demonstrating feasibility and efficacy in assisting individuals with mobility impairments and physical disabilities in object selection tasks.

The P3 event-related potential increases when humans learn a strategy for motor adaptation.

Human motor learning involves cognitive strategies in addition to implicit adaptation. Differences in systems-level neurophysiology between strategy-based and implicit learning remain poorly understood. We asked how the P3 event-related potential, an electroencephalography signal known to increase during early motor learning, relates to strategy-based learning and implicit adaptation. We re-analysed data from two experiments, in which participants (n = 64) reached towards a visual target, with online visual feedback replacing vision of their moving hand. We induced learning by rotating the visual feedback. In the first experiment, feedback rotations were turned on during pairs of two consecutive trials, interspersed between non-rotated trials. In one condition, feedback was rotated relative to the actual movement, allowing participants to develop a re-aiming strategy on the second trial of each pair, while it was rotated relative to the target in the other condition, rendering re-aiming futile. P3 amplitude increased in the first rotated trial in both conditions, but this increase was more pronounced in the re-aiming condition. In the second experiment, a constant visuomotor rotation was turned on for many consecutive trials. We instructed one group beforehand how to re-aim successfully, while the other group had to develop a strategy by themselves. P3 amplitude increased during early adaptation only in the latter group. These findings collectively suggest that in the context of motor learning, the P3 ERP is associated with a need to develop, or adjust, a cognitive strategy.

Social face processing in chronic severe traumatic brain injury: Altered decoding of emotions and mental states but preserved gaze cueing of attention

The processing of social information transmitted by facial stimuli is altered in individuals with traumatic brain injury (TBI). This study investigated whether these alterations also affect the mechanisms underlying the orienting of visual attention in response to eye-gaze signals. TBI patients and a control group of healthy individuals matched on relevant criteria completed a spatial cueing task. In this task, a lateral visual target was presented along with a task-irrelevant face, with the gaze averted to the left or right. Arrows pointing towards the left or right were also used as non-social control stimuli. Social cognition abilities were further investigated through tests based on decoding emotional expressions and mental states conveyed by facial stimuli. The decoding of emotions and mental states was worse in the TBI group than in the control group. However, both groups demonstrated reliable and comparable orienting of attention to both eye-gaze and arrow stimuli. Despite impairments in certain aspects of social face processing among TBI patients, gaze cueing of attention appears to be preserved in this neuropsychological population.

Efficient occlusion avoidance based on active deep sensing for harvesting robots

With the increasing shortage of agricultural labor, the development of harvesting robots is becoming more and more urgent. Most of them require vision to locate the target, however, occlusion is common in agricultural environment, which restricts the accuracy of visual target recognition, and even leads to failure in serious cases. The active perception method is an effective means, but how to efficiently find the best observation position remains difficult to avoid the waste of time caused by repeated invalid motion. Targeting these problems, an active deep sensing method is proposed for harvesting clustered and single fruits. First, the region of interest of the target is extracted by a segmentation network, and then the occlusion status of it is obtained by image processing methods. Taking the current observation position as the starting point, the camera is moved within a matrix to form confidence and occlusion rate distribution maps. After establishing a series of occlusion rate and confidence matrix datasets, a designed deep network has been trained, which is used to predict the maximum confidence/minimum occlusion rate position after the current occlusion status is estimated. To verify the reliability of the method, laboratory and field experiments were carried out for apples and clustered tomatoes. After 1000 times of verification, results show that the successful pick/recognition rate is increased by 38.7 %, and the average successful recognition time is 5.2 s, which is 63.1 % and 46.4 % faster than that of a fixed movement method and a simple heuristic method.

Rapid integration of face detection and task set in visually guided reaching.

The superior colliculus (SC) has been increasingly implicated in the rapid processing of evolutionarily relevant stimuli like faces, but the behavioural relevance of such processing is unclear. The SC has also been implicated in the generation of express visuomotor responses (EVR), which are very short-latency (~80 ms) bursts of muscle activity time-locked to visual target presentation. These observations led us to investigate the influence of faces on EVRs. We recorded upper limb muscle activity from healthy participants as they reached toward targets in the presence of a distractor. In some experiments, faces were used as stimuli. Across blocks of trials, we varied the instruction as to which stimulus served as the target or distractor. Doing so allowed us to assess the impact of instruction on muscle recruitment given identical visual stimuli. We found that responses were uniquely modulated in tasks involving high-contrast faces, promoting reaches toward or away from a face depending on instruction. Follow-up experiments confirmed that the phenomenon required highly salient repeated faces and was not observed to non-facial stimuli nor to faces expressing different affects. This study extends the hypothesis that the SC mediates the EVR by demonstrating that faces impact muscle recruitment at short latencies that precede cortical activity for face perception. Our results constitute direct evidence for the behavioural relevance of face detection in the brainstem, and also implicate a role for top-down cortical pre-setting of the EVR depending on task context.

MIMTracking: Masked image modeling enhanced vision transformer for visual object tracking

Recently, one-stage trackers achieve state-of-the-art tracking results due to more sufficient integration of search and template representations. These methods usually adopt an encoder for synchronous feature generation and interaction. Despite their high performance, the one-stage approaches tend to feed the encoder full input representations that are highly redundant and dense during training. With a focus on tackling this problem, a novel algorithm termed MIMTracking is developed for visual target tracking. MIMTracking exploits an encoder and a decoder for masked image modeling during training. Randomly sampled discrete search embeddings and template embeddings serve as input of the encoder. The lightweight decoder takes full representations as input and progressively highlights the target region. This design alleviates input redundancy and reduces the computational cost of the training process, thereby allowing for more efficient learning of useful representations. The proposed MIMTracking achieves state-of-the-art tracking results on numerous tracking datasets, e.g., 51.5 % area under curve (AUC) on LaSOText, outperforming the previous top tracker OSTrack by 2 %. Especially, our large model MIMTracking-L further improves the AUC to 53.4 % on LaSOText.

Benchmarking automation-aided performance in a forensic face matching task

Carragher and Hancock (2023) investigated how individuals performed in a one-to-one face matching task when assisted by an Automated Facial Recognition System (AFRS). Across five pre-registered experiments they found evidence of suboptimal aided performance, with AFRS-assisted individuals consistently failing to reach the level of performance the AFRS achieved alone. The current study reanalyses these data (Carragher and Hancock, 2023), to benchmark automation-aided performance against a series of statistical models of collaborative decision making, spanning a range of efficiency levels. Analyses using a Bayesian hierarchical signal detection model revealed that collaborative performance was highly inefficient, falling closest to the most suboptimal models of automation dependence tested. This pattern of results generalises previous reports of suboptimal human-automation interaction across a range of visual search, target detection, sensory discrimination, and numeric estimation decision-making tasks. The current study is the first to provide benchmarks of automation-aided performance in the one-to-one face matching task.