Optical Flow Analysis Research Articles

Optokinetic eye movements elicited by radial optic flow in the macaque monkey.

We recorded spontaneous eye movements elicited by radial optic flow in three macaque monkeys using the scleral search coil technique. Computer-generated stimuli simulated forward or backward motion of the monkey with respect to a number of small illuminated dots arranged on a virtual ground plane. We wanted to see whether optokinetic eye movements are induced by radial optic flow stimuli that simulate self-movement, quantify their parameters, and consider their effects on the processing of optic flow. A regular pattern of interchanging fast and slow eye movements with a frequency of 2 Hz was observed. When we shifted the horizontal position of the focus of expansion (FOE) during simulated forward motion (expansional optic flow), median horizontal eye position also shifted in the same direction but only by a smaller amount; for simulated backward motion (contractional optic flow), median eye position shifted in the opposite direction. We relate this to a change in Schlagfeld typically observed in optokinetic nystagmus. Direction and speed of slow phase eye movements were compared with the local flow field motion in gaze direction (the foveal flow). Eye movement direction matched well the foveal motion. Small systematic deviations could be attributed to an integration of the global motion pattern. Eye speed on average did not match foveal stimulus speed, as the median gain was only approximately 0.5-0.6. The gain was always lower for expanding than for contracting stimuli. We analyzed the time course of the eye movement immediately after each saccade. We found remarkable differences in the initial development of gain and directional following for expansion and contraction. For expansion, directional following and gain were initially poor and strongly influenced by the ongoing eye movement before the saccade. This was not the case for contraction. These differences also can be linked to properties of the optokinetic system. We conclude that optokinetic eye movements can be elicited by radial optic flow fields simulating self-motion. These eye movements are linked to the parafoveal flow field, i.e., the motion in the direction of gaze. In the retinal projection of the optic flow, such eye movements superimpose retinal slip. This results in complex retinal motion patterns, especially because the gain of the eye movement is small and variable. This observation has special relevance for mechanisms that determine self-motion from retinal flow fields. It is necessary to consider the influence of eye movements in optic flow analysis, but our results suggest that direction and speed of an eye movement should be treated differently.

Detection and discrimination of optical flow components

Observers viewed animation sequences consisting of random dots, some of which moved coherently in a given direction (signal dots) and the rest of which moved randomly (noise dots). Using forced‐choice procedures, detectability of weak signals within noise was measured for translation, rotation, and expansion/contraction. Sensitivity to all motion types was approximately equal, with practiced observers reliably detecting coherent motion at signal levels as low as 4%. Observers were able to identify the motion structure presented on a given trial at signal levels corresponding to the detection threshold, implying that the neural signals supporting detection are labeled for motion type. Results are discussed in the context of hierarchical analysis of optic flow in which all motion types are registered as patterns of activity among neurons comprising a single mechanism.

120 らせんCTにおける呼吸性移動に関する研究 : Optical Flow解析を用いた肺の呼吸性移動の解析

120 らせんCTにおける呼吸性移動に関する研究 : Optical Flow解析を用いた肺の呼吸性移動の解析

The relationship of vertical and horizontal velocity gradients in the perception of shape, rotation, and rigidity.

Perceived shape, rotation, and rigidity were investigated in displays with linear velocity gradients in the vertical and horizontal directions. Different temporal relationships between these gradients simulated perspective projections of frontally oriented or rotated translating dihedral angles, orthographic projections of rotating dihedral angles, or nonrigid motion. Displays with nonzero horizontal gradients were judged to represent greater angle magnitudes (less relative depth) than displays with 0 horizontal gradients. The temporal relationship between the vertical and horizontal gradients did not influence judged shape but did affect rotation and rigidity judgments; rigid rotations were judged to rotate most, and nonrigid displays were rated as least rigid. These results indicate that the visual system integrates information from more than 1 velocity field. Possible integration methods based on first-order optic flow analysis are discussed.

Optic Flow and Visual Analysis of the Base-to-Final Turn

In the spirit of other optic flow research, we address the problem of how a pilot turns an airplane into alignment with a runway. a maneuver that is one of the more challenging phases of visually controlled flight. In earlier work. Loomis and Beall (1992) proposed a rule for turning an aircraft into alignment: Turn the aircraft in such a way as to hold constant the rate of change of splay (the angle the projected runway makes with respect to the vertical). The experiment presented in this article was a psychophysical test of this rule. We compared day and night landing approaches as our experimental manipulation; we were interested in any role that ground texture might play in the spatial judgment involved in performing the landing approach. Three pilots varying in flight experience performed multiple approaches in a light aircraft for a total of 26 day and 25 night approaches. The 1hree:dimensional trajectories of the aircraft were measured using differential global positioning system data. From these trajectories we computed a variety of motion variables (e.g.. turn rate) and two optic flow variables (splay and splay rate). The similar performance of day and night approaches suggests that the pilots were using optic flow variables that were invariant with changes in the visibility of ground texture. A computer model was developed based on the optic flow rule and estimates of human visual processing thresholds. We conclude that the model gives a good description of pilot performance as tested in our experiment and may help to illuminate the cause of a class of airplane accidents during the common landing phase.

Analysis of optic flow in the monkey parietal area 7a.

Environmentally relevant stimuli were used to examine the selectivity of area 7a neurons to optic flow using moving, flickering dots. Monkeys performed a psychophysical task requiring them to detect changes in translation, rotational and radially structured optic flow fields consisting of collections of moving dots which are free of form cues. The neurons in area 7a were selectively responsive to all the different types of moving stimuli. Two types of tuning for motion selectivity were found. Some neurons were tuned to distinguish a particular direction of optic flow (e.g. radial expansion versus radial compression), while others were tuned to distinguish between different classes of optic flow (e.g. radial motion versus planar rotation). The latter tuning was unlike that reported for area MST by others and may represent a novel representation of optic flow. The response of these neurons to translating bars was compared to that of optic flow fields. There appeared to be no similarity in the tuning to the two types of motion. Furthermore, there does not appear to be an identity between the neurons that could be classified as opponent vector and those selective for radial optic flow. Area 7a is involved in the further analysis of optic flow beyond the cortical areas MT and MST and provides a novel representation of motion. These results are consistent with the neurons in area 7a utilizing motion for the construction of a spatial representation of extra-personal space.

Measuring 3‐D plant growth using optical flow

A method is presented for measuring 3-D plant growth using the optical flow computed on an image sequence of a growing corn seedling. Each image in the sequence consists of two views of the same seedling; one view of the corn seedling is front-on while the second view is a orthogonal view (at 90°) of the seedling made by projecting the plant's orthogonal image onto a mirror oriented at 45° with respect to the camera. We compute 3-D velocity (motion) of the corn seedling's tip by using a simple extension of the 2-D motion constraint equation used in optical flow analysis. This method is an extension of the work presented by Barron and Liptay where optical flow was used to measure the 2-D growth (in the vertical plane) of a corn seedling.

Multiple temporal components of optic flow responses in MST neurons.

Neurons in monkey medial superior temporal cortex (MST) respond to optic flow stimuli with early phasic, tonic, and after-phasic response components. In these experiments we characterized each response component to compare its potential contributions to visual motion processing. The early responses begin 60-100 ms after stimulus onset and last between 100 and 250 ms, the tonic responses begin 100-300 ms after stimulus onset and last for as long as the evoking stimulus persists, and the after-responses begin about 60 ms after the stimulus goes off and last for 100-350 ms. A neuron's tonic responses were evoked by specific optic flow stimuli: over two-thirds of the 264 neurons showed tonic responses evoked by two to five stimuli, whereas only 15% responded to either all or none of the stimuli. The tonic responses continued with stimulus presentations as long as 15 s, with their directional preferences being maintained throughout stimulation. However, the tonic response to a given stimulus was seen to change in amplitude when it was presented in random sequence with different sets of other stimuli. Thus, the tonic responses might convey substantial information about optic flow patterns, which continue with prolonged stimulation, but can be modified by the visual context created by other visual motion stimuli. Only about one-third of the 264 neurons had early responses that were selective for specific stimuli. In neurons yielding at least one early response, that neuron was most often activated by all the visual motion stimuli. After-responses occurred in only half the neurons, but they were more often specifically related to particular optic flow stimuli, regardless of whether those stimuli had evoked tonic excitatory or tonic inhibitory responses. The presence of early and after-responses complicates the interpretation of activity evoked when one stimulus immediately follows another. However, under those conditions, early responses and after-responses might contribute to signaling changes in the ongoing pattern of optic flow. We conclude that several components of MST responses should be recognized and that they potentially play different roles in the cortical analysis of optic flow. Tonic responses show the greatest specificity for particular optic flow stimuli, and possess characteristics which make them suitable neuronal participants in self-movement perception.

Evaluation of Body Motion by Optical Flow Analysis

For quantitative evaluation of body motion, a fully noncontact and unconstraining monitoring method was developed by introducing image sequence analysis. A spatiotemporal local optimization method was applied to determine optical flow in the image sequence. The optical flow visualized the apparent velocity field of the entire body motion, including both breast movement of respiration and posture changes in a bed. The experiment was carried out under regulated posture changes and under a sleeping condition by measuring heart rate, respiration and digitized image sequences using a video camera. A temporal increase in heart rate reflected the magnitude of physical activities. We proposed two candidate parameters for evaluation of respiratory and physical activities based on comparison among experimental results. The average of squared motion velocities reflected the magnitude of physical activities. The representative field-averaged component showed a waveform with periodic fluctuation corresponding to that of respiration obtained with a nasal thermistor.

Medial Superior Temporal Area Neurons Respond to Speed Patterns in Optic Flow

The speed of visual motion in optic flow fields can provide important cues about self-movement. We have studied the speed sensitivities of 131 neurons in the dorsal region of the medial superior temporal area (MSTd) that responded to either radial or circular optic flow stimuli. The responses of more than two-thirds of these neurons were strongly modulated by changes in the mean speed of motion in optic flow stimuli, with response profiles resembling simple filter characteristics. When we removed the normal gradient of speeds in optic flow (slower speeds in the center, faster speeds in the periphery), approximately two-thirds of the neurons showed changes in their responses. When the speed gradient was altered rather than eliminated, almost nine in 10 neurons preferred either a normal speed gradient or an inverted one (slower speeds near the periphery) over stimuli with no speed gradient. These speed gradient preferences do not come simply from different speed preferences in the central and peripheral segments of the stimulus area. Rather, these speed gradient preferences seemed to reflect interactions between simultaneously presented speeds within an optic flow stimulus. The sensitivity of MSTd neurons to patterns of speed, as well as patterns of direction, strengthens the view that these neurons are well suited to the analysis of optic flow. Sensitivity to speed gradients in optic flow might contribute to neuronal mechanisms for spatial orientation during self-movement and for representing the three-dimensional structure of the visual environment.

Detection of apparent skin motion using optical flow analysis: Blood pulsation signal obtained from optical flow sequence

A skin motion imaging system with two modes of operation, diffusive and specular reflections, was developed. The system consists of image capturing and processing elements. Using optical flow analyses of skin motion at the wrist, we have detected successfully a blood pulsation signal that concurs with the electrocardiogram. The signal provides information not only about blood pulsation, but also about blood circulation and the biomechanical properties of the skin. This system may have other applications in the future, such as noncontact blood pulsation detection and evaluation of the biomechanical properties of skin, for example.

Simulated optic flow and extrastriate cortex. I. Optic flow versus texture.

A locomoting observer sees a very different visual scene than an observer at rest: images throughout the visual field accelerate and expand, and they follow approximately radial outward paths from a single origin. This so-called optic flow field is presumably used for visual guidance, and it has been suggested that particular areas of visual cortex are specialized for the analysis of optic flow. In the cat, the lateral suprasylvian visual area (LS) is a likely candidate. To test the hypothesis that LS is specialized for analysis of optic flow fields, we recorded cell responses to optic flow displays. Stimulus movies simulated the experience of a cat trotting slowly across an endless plain covered with small balls. In different simulations we varied the size of balls, their organization (randomly or regularly dispersed), and their color (all one gray level, or multiple shades of gray). For each optic flow movie, a "texture" movie composed of the same elements but lacking optic flow cues was tested. In anesthetized cats, > 500 neurons in LS were studied with a variety of movies. Most (70%) of 454 visually responsive cells responded to optic flow movies. Visually responsive cells generally preferred optic flow to texture movies (69% of those responsive to any movie). The direction in which a movie was shown (forward or reverse) was also an important factor. Most cells (68%) strongly preferred forward motion, which corresponded to visual experience during locomotion.

120 らせんCTにおける呼吸性移動に関する研究 : optical flow解析を用いた肺の呼吸性移動解析(第25回秋季学術大会一般研究発表予稿集)

120 らせんCTにおける呼吸性移動に関する研究 : optical flow解析を用いた肺の呼吸性移動解析(第25回秋季学術大会一般研究発表予稿集)

Visual control of braking in goal-directed action and sport

Reaching a moving object, avoiding an obstacle, or controlling a rotation are common requirements of experts in sport and goal-directed action. Since the original analysis of optic flow, a large number of studies have addressed the problem of perception and control of braking. In this paper, the perception-action strategies described for deceleration control are reviewed; driving, docking, landing, somersaulting, running and reaching are analysed. The role played by 'tau dot', the first temporal derivative of tau, is shown to be critical. However, the so-called constant tau-dot strategy proposed to explain how we regulate our deceleration in such circumstances is critically examined and rejected. New directions in the problem of braking control are proposed that emphasize: (1) the advantage of tau-dot over other kinematic variables; (2) the task specificity of tau-dot; (3) the need to consider tau-dot as a control variable; and (4) the role played by the controller dynamics in the perception - action loop. Several directions for future research are suggested.

Robustness of perception of heading from optic flow

Heading discrimination in optic flow stimuli was investigated in 5 humans. Flow patterns consisted of a computer generated motion sequence which showed a mixture of randomly moving and coherently-moving points. The motion of the coherently-moving fiducial points was completely determined by the changing position of the observer's simulated vantage point. Ego-rotation as well as ego-translation was simulated. Noise and fiducial points were confined to the ground plane in most experiments. In one experiment the points formed a cloud with no visible horizon. The results indicate that heading perception is robust against degradation of the flow-field by the presence of noise or by the reduction of the lifetime of the fiducial points. The results suggest that points, which move independently from the reference frame as formed by the fiducial points, are to a large extent removed from the analysis of optic flow by the visual process which derives the heading. The motion of recognizable points at infinity (like the horizon) appears to be essential for robust heading perception in the presence of ego-rotations.

Dynamic aspects in active vision

The term active stresses the role of the motion or, generally speaking, the dynamic interaction of the observer with the environment. This concept emphasizes the relevance of determining scene properties from the temporal evolution of image features. Within the active vision approach, two different aspects are considered: the advantages of space-variant vision for dynamic visual processing and the qualitative analysis of optical flow. A space-variant sampling of the image plane has many good properties in relation to active vision. In particular, two examples are presented in which a log-polar representation is used for active vergence control and to estimate the time-to-impact during tracking egomotion. These are just two modules which could fit into a complete active vision system, but already highlight the advantages of space-variant sensing within the active vision paradigm. In the second part of the paper the extraction of qualitative properties from the optical flow is discussed. A new methodology is proposed in which optical flows are analyzed in terms of anomalies as unexpected velocity patterns or inconsistencies with respect to some predicted dynamic feature. Two kinds of knowledge are necessary: about the dynamic of the scene (for example, the approximate motion of the camera) and about the task to be accomplished, which is analogous to (qualitatively) knowing the kind of scene I would expect to see. The first simply implies the measurement of some motion parameters (for example, with inertial sensors) directly on the camera, or to put some constraints in the egomotion. The second requirement implies that the visual process is task-driven. Some examples are presented in which the method is successfully applied to robotic tasks.

Use of a distracting task to obtain defensive head movements to looming visual stimuli by human adults in a laboratory setting.

Defensive responses to looming visual stimuli have been obtained in a wide variety of species, including human infants as young as one week. This phenomenon has not, however, been formally demonstrated for adults under laboratory conditions. In this paper it is reported that similar responses, namely avoidance movements of the head, can be obtained in most human adults provided that they are suitably distracted by playing a computer tracking game. Such behaviours were not obtained when subjects were not so distracted. The use of control conditions also ruled out the possibility that simple movement cues from stimuli presented on a noncollision trajectory are sufficient stimulus to obtain defensive responses. It is of interest to note that latencies for avoidance movements were significantly shorter than those for orienting movements in the same situation, but were no different from the latencies for orienting movements when subjects were not distracted. It is argued that these findings are consistent with the proposition that defensive head movements to looming stimuli, like orienting movements to novel peripheral stimuli, represent a basic visual competence that is normally suppressed (or subsumed) by higher competences. The decision to avoid is probably based on the computation of time to contact, and may reflect the operation of a subcortical system for elementary analysis of optic flow.

First-order analysis of optical flow in monkey brain.

Optical flow is a rich source of information about the three-dimensional motion and structure of the visual environment. Little is known of how the brain derives this information. One possibility is that it analyzes first-order elementary components of optical flow, such as expansion, rotation, and shear. Using a combination of physiological recordings and modeling techniques, we investigated the contribution of the middle superior temporal area (MST), a third-order cortical area in the dorsal visual pathway that receives inputs from the medial temporal area (MT). The results show (i) that MST cells, but not MT cells, are selective for elementary flow components (EFCs) alone or their combination with translation, (ii) that MST cells selective for an EFC do not extract this component from a more complex motion pattern, and (iii) that position invariance as observed in MST is compatible with an input arrangement from MT cells matching the selectivity of MST neurons.

Projection-based approach to image analysis: pattern recognition and representation in the position-orientation space

A method for image analysis, based on the formalism of functional analysis is proposed. This approach, which is employed for pattern recognition in the combined position-orientation space, is motivated by a variety of neurophysiological findings that emphasize the importance of the orientation feature in visual image processing and analysis. The approach is applied to the so-called Glass patterns, which are special cases of images characterized uniquely by their orientational feature of local correlations between pairs of corresponding dots. The approach can be of interest in the analysis of optical flow. >

Optical Flow Analysis Based on Spatio‐Temporal Correlation of Dynamic Image

AbstractWe propose several methods for analyzing the velocity of moving particles in dynamic images. The methods are based on the analysis of temporal mutual‐correlation between the time series of gray level changes at a target pixel and that of its neighboring pixels on an image plane. In this paper, we clarify that the temporal mutual‐correlation functions can be understood as the intersections of a kind of spatial autocorrelation of an image irradiance function which is assumed to be rigid. According to this new understanding and assuming a Gaussian‐like decrease in the spatial autocorrelation, we clarify a relation between the correlation‐value and the lag‐time of the mutual‐correlation and velocity of a moving object. This relation results in an improved method for determining the optical flow.Our previous methods are useful only for the analysis of spherical particle motion. However, the improved one can be applied to more general objects. From the analysis of the artificial image sequences, it is suggested that the accuracy of the obtained result is less than 0.01 ±0.01 p/f in speed and 1.0 ±2.0 deg in direction. These results indicate that the improved method has ten times the accuracy of the typical method called the “gradient method.” The improved method is also evaluated by analyzing an actual dynamic scene and confirmed to have the capability to measure the two‐dimensional velocity field (i.e., optical flow).