Motion Judgments Research Articles

Embeddedness of Earth's gravity in visual perception.

Falling objects are commonplace in daily life, requiring precise perceptual judgments for interception and avoidance. We argue that human judgments of projectile motion arise from the interplay between sensory information and predictions constrained by Newtonian mechanics. Our study investigates how individuals perceive falling objects under various gravitational conditions, aiming to understand the role of internalized gravity in visual perception. Through meticulously controlling the available information, we demonstrated that these phenomena cannot be explained solely by simple heuristics nor representational momentum. Instead, we found that the perceptual judgments of humans (n = 11, 13, 14, and 11, respectively, in Experiments 1, 2, 3, and 4) are influenced by a combination of sensory information and gravity predictions, highlighting the role of internalized physical constraints in the perception of projectile motion.

Bubbles-induced turbulence channel prediction mechanism based on machine vision in underwater wireless optical communication.

Bubbles-induced turbulence poses a significant challenge to the stability of underwater wireless optical communication (UWOC) system. Existing methods for understanding channel characteristics rely on the pilot information from the feed-back channel, which are ineffective and inaccurate due to the rapidly changing nature of the underwater channel. We propose a machine-vision-based channel prediction mechanism which contains three modules of motion judgment module, image processing module and scintillation index (SI) prediction module. The mechanism captures images of bubbles and calculates the bubble density. Subsequently, a relational function is applied to acquire the predicted SI which quantifies the impacts of bubbles on the channel. Experimental results validate the effectiveness of the proposed mechanism.

Explicit effort may not influence perceptuomotor decision-making.

Many decisions that humans make are enacted by the action system. For example, humans use reach-to-grasp movements when making perceptuomotor decisions between and obtaining fruits of varying quality from a pile. Recent work suggests that the characteristics of each action alternative may influence the decision itself-there may be a bias away from making perceptuomotor alternatives associated with high effort when participants are unaware of the effort differences between responses. The present study examined if perceptuomotor decisions were influenced by explicit reaching effort differences. Neurotypical human participants were presented with random dot motion stimuli in which most dots moved in random directions and varying percentages of remaining dots moved coherently left- or rightward. Participants reported leftward motion judgements by performing leftward (or left hand) reaching movements and rightward motion judgements by performing rightward (or right hand) reaching movements. A resistance band was affixed to participants' wrists and to the table in different configurations. The configurations allowed for one movement/motion direction judgement to always require stretching of the band and, therefore, require relatively more effort. Across a set of experiments, the response context (i.e. selecting directions within a limb or selecting between limbs) and the effort difference between responses were manipulated. Overall, no experiment revealed a bias away from the perceptuomotor decision associated with high effort. Based on these results, it is concluded that, in this biomechanical context, explicit effort may not influence perceptuomotor decision-making and may point to a contextual influence of action effort on perceptuomotor decision-making.

The contribution of image minification to discomfort experienced in wearable optics.

Wearable optics have a broad range of uses, for example, in refractive spectacles and augmented/virtual reality devices. Despite the long-standing and widespread use of wearable optics in vision care and technology, user discomfort remains an enduring mystery. Some of this discomfort is thought to derive from optical image minification and magnification. However, there is limited scientific data characterizing the full range of physical and perceptual symptoms caused by minification or magnification during daily life. In this study, we aimed to evaluate sensitivity to changes in retinal image size introduced by wearable optics. Forty participants wore 0%, 2%, and 4% radially symmetric optical minifying lenses binocularly (over both eyes) and monocularly (over just one eye). Physical and perceptual symptoms were measured during tasks that required head movement, visual search, and judgment of world motion. All lens pairs except the controls (0% binocular) were consistently associated with increased discomfort along some dimension. Greater minification tended to be associated with greater discomfort, and monocular minification was often-but not always-associated with greater symptoms than binocular minification. Furthermore, our results suggest that dizziness and visual motion were the most reported physical and perceptual symptoms during naturalistic tasks. This work establishes preliminary guidelines for tolerances to binocular and monocular image size distortion in wearable optics.

Response to Asirvatham (2023): Effects of Robot-Assisted Rehabilitation on Hand Function of People With Stroke.

In Thajus Asirvatham’s letter to the editor, one concern expressed was that, in our 2021 study (Lee et al., 2021), sensory function should have been highlighted as much as motor function. In this response, we add some discussion about sensory function.Sensorimotor function is significantly correlated with Fugl-Meyer Assessment–Upper Extremity (FMA–UE; Duncan et al., 1983) scores, which could affect the interlimb coordination and accuracy of limb positioning during movement. The sensory function did not show significant improvement in our study, which may be due to the motor-focused training that we used. Sensorimotor-focused training should be considered.We argue that the discussion of sensorimotor function was partially presented in the article. In our study, sensorimotor function was significantly associated with FMA–UE scores (Nordin et al., 2014), which may affect interlimb coordination and accuracy of limb positioning during movement. The results of our study showed no statistically significant improvement in sensory function in stroke patients with sensory impairment after robotic therapy. Previous studies have shown considerable improvements in proprioceptive acuity using rehabilitation robots with vibro-tactile feedback (Elangovan et al., 2019). The training in our study improved the use of proprioceptive input, resulting in better perceptual judgments of passive motion. Our program focused on motor training, but on the basis of the Semmes–Weinstein hand monofilament and the modified Nottingham Sensory Assessment (University of Nottingham, 2007), this may not have been beneficial for sensory function. Sensorimotor-focused training can be considered in future research. The second concern Asirvatham expressed was related to performance- or function-based assessment, such as the Action Research Arm Test (ARAT; McDonnell, 2008) or the Jebsen–Taylor Hand Function Test (JTT; Jebsen et al., 1969). We agree that, rather than using self-report or impairment-based measures to assess hand function, performance- or function-based assessments, such as the ARAT or the JTT, could be used. In our study, the Box and Block Test (Chen et al., 2009) and grip strength meter were functional assessments, and these tools were readily available in our clinical setting. The use of the ARAT and JTT will be considered in future studies.We thank Asirvatham for the insightful comments about our study, and we appreciate the attention we have received from other readers. Some suggestions have been made about adjustments that we need to make in future studies, and we appreciate the opportunity to respond.

Fundamentally different representations of color and motion revealed by individual differences in perceptual scaling

The coordinate frames for color and motion are often defined by three dimensions (e.g., responses from the three types of human cone photoreceptors for color and the three dimensions of space for motion). Does this common dimensionality lead to similar perceptual representations? Here we show that the organizational principles for the representation of hue and motion direction are instead profoundly different. We compared observers' judgments of hue and motion direction using functionally equivalent stimulus metrics, behavioral tasks, and computational analyses, and used the pattern of individual differences to decode the underlying representational structure for these features. Hue judgments were assessed using a standard "hue-scaling" task (i.e., judging the proportion of red/green and blue/yellow in each hue). Motion judgments were measured using a "motion-scaling" task (i.e., judging the proportion of left/right and up/down motion in moving dots). Analyses of the interobserver variability in hue scaling revealed multiple independent factors limited to different local regions of color space. This is inconsistent with the influences across a broad range of hues predicted by conventional color-opponent models. In contrast, variations in motion scaling were characterized by more global factors plausibly related to variation in the relative weightings of the cardinal spatial axes. These results suggest that although the coordinate frames for specifying color and motion share a common dimensional structure, the perceptual coding principles for hue and motion direction are distinct. These differences might reflect a distinction between the computational strategies required for the visual analysis of spatial vs. nonspatial attributes of the world.

Causality modulates perception of apparent motion stimuli

Previous studies have shown that contextual information can alter judgments of apparent motion. Specifically, the presence of causal information can even override the shortest-path bias, if the shortest path is inconsistent with a causal interpretation of the motion event. While these results demonstrate that judgments of apparent motion are affected by causality, how causality modulates lower-level spatiotemporal processing is not yet understood. Moreover, it is unclear whether subjects’ judgments of apparent motion are the result of perceptual processing or higher-level reasoning. Addressing these questions, we investigated whether causal information could influence detection sensitivity in an apparent motion display. Our apparent motion displays involved two vertically stacked semicircular tubes, and contextual information suggested either motion through the top or bottom tube. Each tube contained a small aperture that would flash, appearing as if the launched object was briefly visible along the motion-path. In addition, contextual information could also be inconsistent with the flash location. In our first experiment, participants judged the location of the target flash under causal and non-causal conditions. In experiment 2, we compared the effect of causality with motion priming, a noncausal cue that may covary with the causal cue. In both experiments, detection was most influenced by causal information, being most accurate when causality was consistent with the target flash and least accurate when causal information acted as a distractor– suggesting that the visual system generates spatiotemporal predictions of object motion during perceived causal interactions.

Perception of object motion during self-motion: Correlated biases in judgments of heading direction and object motion.

This study investigated the relationship between perceived heading direction and perceived motion of an independently moving object during self-motion. Using a dual task paradigm, we tested whether object motion judgments showed biases consistent with heading perception, both across conditions and from trial to trial. Subjects viewed simulated self-motion and estimated their heading direction (Experiment 1), or walked toward a target in virtual reality with conflicting physical and visual cues (Experiment 2). During self-motion, an independently moving object briefly appeared, with varied horizontal velocity, and observers judged whether the object was moving leftward or rightward. In Experiment 1, heading estimates showed an expected center bias, and object motion judgments showed corresponding biases. Trial-to-trial variations were also correlated: on trials with a more rightward heading bias, object motion judgments were consistent with a more rightward heading, and vice versa. In Experiment 2, we estimated the relative weighting of visual and physical cues in control of walking and object motion judgments. Both were strongly influenced by nonvisual cues, with less weighting for object motion (86% vs. 63%). There were also trial-to-trial correlations between biases in walking direction and object motion judgments. The results provide evidence that shared mechanisms contribute to heading perception and perception of object motion.

Multiple object tracking in farmland based on fusion point cloud data

Object detection and tracking in a farmland environment is greatly important to unmanned agricultural machinery navigation technology. Based on the existing methods of fusion point cloud acquisition and object detection, the multiple object tracking method was further researched. Constant velocity model was selected as the motion model, and state estimation was achieved using Kalman filter. Data association between the detectors and trackers was realized through an improved GNN method based on the cost of category conversion. A tracking state machine and two threshold mechanisms were proposed to avoid “combined explosion” disaster. Fusion point cloud data were used for motion judgment to achieve the real motion attributes and speed of the objects based on ground reference. As the results, the average static drift of the tracking method was less than 6.5 cm, the discrimination accuracy of static objects exceeded 75%. Besides, the multiple object tracking precision was less than 35 cm, and the multiple object tracking accuracy exceeded 85%. Therefore, the proposed multiple object tracking method could satisfy the requirements in the farmland environment.

Investigating the role of working memory resources across aesthetic and non-aesthetic judgements.

Aesthetic judgements dominate much of daily life by guiding how we evaluate objects, people, and experiences in our environment. One key question that remains unanswered is the extent to which more specialised or largely general cognitive resources support aesthetic judgements. To investigate this question in the context of working memory, we examined the extent to which a working memory load produces similar or different response time interference on aesthetic compared with non-aesthetic judgements. Across three pre-registered experiments that used Bayesian multi-level modelling approaches (N > 100 per experiment), we found clear evidence that a working memory load produces similar response time interference on aesthetic judgements relative to non-aesthetic (motion) judgements. We also showed that this similarity in processing across aesthetic versus non-aesthetic judgements holds across variations in the form of art (people vs. landscape; Experiments 1-3), medium type (artwork vs. photographs; Experiment 2), and load content (art images vs. letters; Experiments 1-3). These findings suggest that across a range of experimental contexts, as well as different processing streams in working memory (e.g., visual vs. verbal), aesthetic and motion judgements commonly rely on a domain-general cognitive system, rather than a system that is more specifically tied to aesthetic judgements. In doing so, these findings shine new light on the working memory resources that support aesthetic judgements, as well as on how domain-general cognitive systems operate more generally in cognition.

Functional specificity and neural integration in the aesthetic appreciation of artworks with implied motion.

Although there is growing interest in the neural foundations of aesthetic experience, it remains unclear how particular mental subsystems (e.g. perceptual, affective and cognitive) are involved in different types of aesthetic judgements. Here, we use fMRI to investigate the involvement of different neural networks during aesthetic judgements of visual artworks with implied motion cues. First, a behavioural experiment (N = 45) confirmed a preference for paintings with implied motion over static cues. Subsequently, in a preregistered fMRI experiment (N = 27), participants made aesthetic and motion judgements towards paintings representing human bodies in dynamic and static postures. Using functional region-of-interest and Bayesian multilevel modelling approaches, we provide no compelling evidence for unique sensitivity within or between neural systems associated with body perception, motion and affective processing during the aesthetic evaluation of paintings with implied motion. However, we show suggestive evidence that motion and body-selective systems may integrate signals via functional connections with a separate neural network in dorsal parietal cortex, which may act as a relay or integration site. Our findings clarify the roles of basic visual and affective brain circuitry in evaluating a central aesthetic feature-implied motion-while also pointing towards promising future research directions, which involve modelling aesthetic preferences as hierarchical interplay between visual and affective circuits and integration processes in frontoparietal cortex.

Application of Computer Visual Recognition in Industrial Automation Assembly Production Line

Computer vision recognition technology refers to the technology of simulating human vision system with computer to realize the functions of object recognition, shape orientation confirmation, motion judgment and so on, in order to adapt, understand the external environment and control their own motion. The present situation of industrial automation in China is that the industries covered by full automation are relatively limited, mainly concentrated in the high value-added industries represented by automobiles, and most industries choose simple automation according to the tradeoff between automation effect and cost. In the course of industrial automation, the corresponding control technology and the most representative programmable controller, industrial computer and intelligent instrument device are developed according to the main characteristics of industrial field, among which computer vision recognition technology is more and more widely used in industrial automation.

Optimization of Intelligent English Pronunciation Training System Based on Android Platform

Oral English, as a language tool, is not only an important part of English learning but also an essential part. For nonnative English learners, effective and meaningful voice feedback is very important. At present, most of the traditional recognition and error correction systems for oral English training are still in the theoretical stage. At the same time, the corresponding high-end experimental prototype also has the disadvantages of large and complex system. In the speech recognition technology, the traditional speech recognition technology is not perfect in recognition ability and recognition accuracy, and it relies too much on the recognition of speech content, which is easily affected by the noise environment. Based on this, this paper will develop and design a spoken English assistant pronunciation training system based on Android smartphone platform. Based on the in-depth study and analysis of spoken English speech correction algorithm and speech feedback mechanism, this paper proposes a lip motion judgment algorithm based on ultrasonic detection, which is used to assist the traditional speech recognition algorithm in double feedback judgment. In the feedback mechanism of intelligent speech training, a double benchmark scoring mechanism is introduced to comprehensively evaluate the speech of the speech trainer and correct the speaker’s speech in time. The experimental results show that the speech accuracy of the system reaches 85%, which improves the level of oral English trainers to a certain extent.

Proposal of Motion Judgment Algorithm Based on Joint Angle of Variable Elastic Assist Suit with High Back Drivability

In recent years, the burden per worker has increased due to a decrease in the working population. Wearable assist suits have been developed as one of the methods for solving the problem. To extend the assist suit to practical situations, it is necessary to provide a motion judgment interface for judging the motion of a wearer. Therefore, in our study, a motion judgment algorithm is proposed for assist suits, based on variable viscoelasticity. The proposed algorithm judges sitting, standing-up, stance, sitting-down, and gait using only the joint angle information of the suit and verification is performed using human joint angles obtained by motion capture. Thus, the motion judgment rate is 90% or more for sitting, standing-up, stance, and sitting-down, and 80% or more for gait, confirming the usefulness of motion judgment. Additionally, based on these results, further verification is performed on an actual machine. As a result, in a series of motions starting from the sitting to the standing-up, the stance, and the gait, the motion judgement is successful five times from the sitting to the standing-up, the stance, and once in gait. In a series of motions from sitting to standing-up, the stance, and sitting-down, the motion judgment is successful five times during sitting; five times during sitting, stance, and sitting-down; and three times during standing-up. In this way, it is confirmed that the proposed method can judge the motion only by angle information, although there is a problem in a success rate depending on the motion.

Trait anxiety is linked to increased usage of priors in a perceptual decision making task

Current predictive processing accounts consider negative affect to result from elevated rates of prediction error, thereby motivating changes in the degree with which prior expectancies and sensory evidence influence our perceptions. Trait anxiety is associated with the amount of negative affect a person is experiencing and has been linked to aberrant strategies in decision making and belief updating. Here, we assessed the degree to which induced prior expectancies influenced motion judgements in a simple perceptual decision making task in 117 healthy participants with varying levels of trait anxiety. High trait anxious individuals showed increased usage of priors, independent from the amount of sensory uncertainty that was perceived. This finding demonstrates aberrant strategies of belief updating in anxiety even in evaluating nonthreatening visual motion stimuli, and thus suggest an influential role of affective traits in processes of perceptual inference.

A Classification Method for Unrecognized Spatial Disorientation Based on Perceptual Process

Spatial disorientation (SD) is the pilot's wrong judgment of flight altitude, position, and motion in three-dimensional space during flight. SD is among the significant causes of flight accidents that seriously affect flight safety. Unrecognized SD causes most of these accidents. In this study, we analyzed the mechanism of unrecognized SD based on the brain's perceptual process. According to the process of sensation and perception, we put forth a new hypothesis of a classification method for unrecognized SD: unrecognized SD might be subdivided into insensate SD, unperceived SD, and perceived SD. There might be some meaningful differences in brain activity in EEG signals or fMRI between unperceived SD and perceived SD. The classification method in this study was proposed based on some related research reports and provided new ideas and methods for scholars to study unrecognized SD. If the hypothesis can be proved, it will provide a basis for scholars learning the mechanism of unrecognized SD and subsequently putting forward countermeasures in SD training. Moreover, as a consequence, the subdivision will contribute to pilot selection, and some specialized SD training for countermeasures could be put forward to reduce aircraft accidents.

A model of how depth facilitates scene-relative object motion perception.

Many everyday interactions with moving objects benefit from an accurate perception of their movement. Self-motion, however, complicates object motion perception because it generates a global pattern of motion on the observer’s retina and radically influences an object’s retinal motion. There is strong evidence that the brain compensates by suppressing the retinal motion due to self-motion, however, this requires estimates of depth relative to the object—otherwise the appropriate self-motion component to remove cannot be determined. The underlying neural mechanisms are unknown, but neurons in brain areas MT and MST may contribute given their sensitivity to motion parallax and depth through joint direction, speed, and disparity tuning. We developed a neural model to investigate whether cells in areas MT and MST with well-established neurophysiological properties can account for human object motion judgments during self-motion. We tested the model by comparing simulated object motion signals to human object motion judgments in environments with monocular, binocular, and ambiguous depth. Our simulations show how precise depth information, such as that from binocular disparity, may improve estimates of the retinal motion pattern due the self-motion through increased selectivity among units that respond to the global self-motion pattern. The enhanced self-motion estimates emerged from recurrent feedback connections in MST and allowed the model to better suppress the appropriate direction, speed, and disparity signals from the object’s retinal motion, improving the accuracy of the object’s movement direction represented by motion signals.

Frontal cortex selectively overrides auditory processing to bias perception for looming sonic motion

Rising intensity sounds signal approaching objects traveling toward an observer. A variety of species preferentially respond to looming over receding auditory motion, reflecting an evolutionary perceptual bias for recognizing approaching threats. We probed the neural origins of this stark perceptual anisotropy to reveal how the brain creates privilege for auditory looming events. While recording neural activity via electroencephalography (EEG), human listeners rapidly judged whether dynamic (intensity varying) tones were looming or receding in percept. Behaviorally, listeners responded faster to auditory looms confirming a perceptual bias for approaching signals. EEG source analysis revealed sensory activation localized to primary auditory cortex (PAC) and decision-related activity in prefrontal cortex (PFC) within 200 ms after sound onset followed by additional expansive PFC activation by 500 ms. Notably, early PFC (but not PAC) activity rapidly differentiated looming and receding stimuli and this effect roughly co-occurred with sound arrival in auditory cortex. Brain-behavior correlations revealed an association between PFC neural latencies and listeners’ speed of sonic motion judgments. Directed functional connectivity revealed stronger information flow from PFC → PAC during looming vs. receding sounds. Our electrophysiological data reveal a critical, previously undocumented role of prefrontal cortex in judging dynamic sonic motion. Both faster neural bias and a functional override of obligatory sensory processing via selective, directional PFC signaling toward auditory system establish the perceptual privilege for approaching looming sounds.

Encoding- and decision-related brain activity during a motion judgment task

We have previously used steady-state VEPs to show that responses in visual cortex are strongly suppressed when motion stimuli produce inter-ocular velocity differences (Kohler et al., 2018), regardless of whether these differences give rise to movement in depth (MID). Here we used an event-related VEP design to explore how activity evoked by lateral movement and MID unfolds over time. Participants (n=20) viewed stereoscopically presented random-dot patterns in which a central region moved in one of four directions. Dots underwent single-shot apparent motion on every trial: in-phase motion between the two eyes produced lateral movement (left/right), while anti-phase motion gave rise to MID (towards/away). Participants indicated movement direction as quickly and accurately as possible using the keyboard arrow keys. For lateral movement, accuracy was at ceiling and reaction time (RT) was ~800ms, while MID produced lower accuracies (~80%) and longer RTs (~1000ms). We used reliable components analysis to extract maximally correlated signal components from the EEG data (Dmochowski et al., 2012). A medio-frontal component appeared to capture decision-related activity, exhibiting a ramp-like shape that was shallower for MID, consistent with a longer integration period leading to slower RTs. An additional component, centered over occipital cortex, appeared to primarily capture encoding-related activity. Lateral movement and MID produced indistinguishable positive peaks at ~70ms, but diverged at later negative (~180ms) and positive (~350ms) peaks. MID responses were enhanced (more negative) around the negative peak (100–200ms) and suppressed (less positive) leading up to the second positive peak (250–350ms). This late-onset suppression is consistent with the finding that suppression depends on second-order processes, including extraction of relative motion and relative disparity (Kohler et al., 2018). The current results provide a time-resolved electrophysiological analogue to psychophysical data showing that temporal integration underlying decision making is near-perfect for lateral motion, but sub-optimal for MID (Katz et al., 2015).

Auditory capture of visual apparent motion, both laterally and looming

Traditional tests of multisensory stimuli typically support that vision dominates spatial judgments and audition dominates temporal ones. Here, we examine if unambiguous auditory spatial cues can capture ambiguous visual ones in judgments of direction of apparent motion. The visual motion judgments include both lateral movement and movement in depth, each when coupled with auditory stimuli moving at one of four rates. Experiment 1 tested lateral visual movement judgments (leftward vs rightward) coupled with auditory stimuli that moved laterally. Experiment 2 tested depth visual movement judgments (approaching vs receding) coupled with auditory stimuli that got louder or quieter. Results of Experiment 1 revealed and replicated an overall leftward motion bias, but with additional acoustic capture to experience visual movement away from the side on which sound initially occurred, and no effect of auditory motion speed. Results of Experiment 2 revealed and replicated an approaching motion bias, but with no effect of initial sound intensity, and an additional systematic capture effect of auditory motion speed. Faster changes in acoustic intensity produced larger visual motion capture consistent with the direction of acoustic intensity change. Findings of both experiments generalized over conditions of listening device (head phones vs speakers) and test-setting (Laboratory vs Web-based data-collection). The leftward and approaching motion bias results replicate previous research. Our principal new findings, the auditory motion capture effects, confirm the multisensory nature of dynamic spatial perception and support that extent of inter-sensory capture is a function of the relative reliability of spatial information acquired by each sensory modality.