The interpretation of biological motion

Hoffman, Donald D.; Flinchbaugh, Bruce E.

doi:10.1007/bf00340076

Cited by 198 publications

(17 citation statements)

References 3 publications

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“…In the above sections and within this investigation we have presented techniques for background generation and calibration to improve the previously developed simulation model. Even though extracting information about human characteristics from video recording may still be in its infancy, it is important to mention that the field of human motion analysis is large and has a history traced back to the work of Hoffman and Flinchbaugh [27]. In the field of pedestrian detection techniques, moreover in the big area of computer vision, many problems have accumulated.…”

Section: Conclusion and Possible Improvementmentioning

confidence: 99%

Tracking Individual Targets in High Density Crowd Scenes Analysis of a Video Recording in Hajj 2009

Dridi¹

2015

CUS

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In this paper we present a number of methods (manual, semi-automatic and automatic) for tracking individual targets in high density crowd scenes where thousand of people are gathered. The necessary data about the motion of individuals and a lot of other physical information can be extracted from consecutive image sequences in different ways, including optical flow and block motion estimation. One of the famous methods for tracking moving objects is the block matching method. This way to estimate subject motion requires the specification of a comparison window which determines the scale of the estimate. In this work we present a real-time method for pedestrian recognition and tracking in sequences of high resolution images obtained by a stationary (high definition) camera located in different places on the Haram mosque in Mecca. The objective is to estimate pedestrian velocities as a function of the local density.The resulting data of tracking moving pedestrians based on video sequences are presented in the following section. Through the evaluated system the spatio-temporal coordinates of each pedestrian during the Tawaf ritual are established. The pilgrim velocities as function of the local densities in the Mataf area (Haram Mosque Mecca) are illustrated and very precisely documented.Tracking in such places where pedestrian density reaches 7 to 8 Persons/m 2 is extremely challenging due to the small number of pixels on the target, appearance ambiguity resulting from the dense packing, and severe inter-object occlusions. The tracking method which is outlined in this paper overcomes these challenges by using a virtual camera which is matched in position, rotation and focal length to the original camera in such a way that the features of the 3D-model match the feature position of the filmed mosque. In this model an individual feature has to be identified by eye, where contrast is a criterion. We do know that the pilgrims walk on a plane, and after matching the camera we also have the height of the plane in 3D-space from our 3D-model. A point object is placed at the position of a selected pedestrian. During the animation we set multiple animation-keys (approximately every 25 to 50 frames which equals 1 to 2 seconds) for the position, such that the position of the point and the pedestrian overlay nearly at every time. By combining all these variables with the available appearance information, we are able to track individual targets in high density crowds.

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Section: Conclusion and Possible Improvementmentioning

confidence: 99%

Tracking Individual Targets in High Density Crowd Scenes Analysis of a Video Recording in Hajj 2009

Dridi¹

2015

CUS

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“…UUman (1979) showed that under a rigidity constraint, three views of four noncoplanar points are sufficient to recover structure in an orthographic projection, up to a reflection about the frontal plane. The required numbers of points and views are reduced by adding further constraints, such as planarity (Hoffman & Flinchbaugh, 1982), fixed axis of rotation (Hoffman & Bennett, 1986;Webb & Aggarwal, 1981), and constant angular velocity (Hoffman & Bennett, 1985). These proofs are summarized in Table 1.A number of empirical studies have addressed issues related to theoretical analyses of the recovery of structure from motion.…”

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confidence: 99%

Minimum points and views for the recovery of three-dimensional structure.

Braunstein¹,

Hoffman²,

Shapiro³

et al. 1987

Journal of Experimental Psychology: Human Perception and Perfor

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Mathematical analyses of motion perception have established minimum combinations of points and distinct views that are sufficient to recover three-dimensional (3D) structure from two-dimensional (2D) images, using such regularities as rigid motion, fixed axis of rotation, and constant angular velocity. To determine whether human subjects could recover 3D information at these theoretical levels, vie presented subjects with pairs of displays and asked them to determine whether they represented the same or different 3D structures. Number of points was varied between two and five; number of views was varied between two and six; and the motion was fixed axis with constant angular velocity, fixed axis with variable velocity, or variable axis with variable velocity. Accuracy increased with views, decreased with points, and was greater with fixed-axis motion. Subjects performed above chance levels even when motion was eliminated, indicating that they exploited regularities in addition to those in the theoretical analyses.Theoretical investigations of visual motion have provided a number of specific analyses of the minimum number of points and views required to recover three-dimensional (3D) structure from two-dimensional (2D) images. Recovery of 3D structure, in this context, is denned as determining the x, y, and z coordinates of each point, up to a scale factor. These analyses differ in the constraints that are imposed. UUman (1979) showed that under a rigidity constraint, three views of four noncoplanar points are sufficient to recover structure in an orthographic projection, up to a reflection about the frontal plane. The required numbers of points and views are reduced by adding further constraints, such as planarity (Hoffman & Flinchbaugh, 1982), fixed axis of rotation (Hoffman & Bennett, 1986;Webb & Aggarwal, 1981), and constant angular velocity (Hoffman & Bennett, 1985). These proofs are summarized in Table 1.A number of empirical studies have addressed issues related to theoretical analyses of the recovery of structure from motion. Several studies (e.g., Braunstein & Andersen, 1986;Schwartz & Sperling, 1983;Todd, 1985) have questioned the generality of the rigidity constraint. Other studies have considered the recovery of structure with small numbers of views or with small numbers of points. Lappin, Doner, and Kotlas (1980) found that subjects could make accurate judgments based on 3D structure This research was supported by a contract to D. Hoffman from the Office of Naval Research, Cognitive and Neural Sciences Division, Perceptual Sciences Group. We thank Joseph Lappin and James Todd for helpful comments on an earlier version of this article and Johnna Eastbum and James Tittle for assistance in various aspects of this research.

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“…Visible parts are in general not arbitrary; instead the likelihood of their locations depends on the structure of the underlying object. 3 Another way to think about SI information is to compare it to the assumption of pairwise rigid planar motions (Hoffman & Flinchbaugh, 1982) or fixed-axis motions (Hoffman & Bennett, 1986). The first assumption has been introduced in the context of biological motion to explain the level of performance in recognizing the motion of terrestrial bipeds and quadrupeds.…”

Section: Discussionmentioning

confidence: 99%

“…More specifically, the assumption that two points are rigidly connected (a fixed axis) and rotating in a plane makes the structure recoverable from three orthographic projections. Three points forming two hinged pairs are recoverable from only two projections (Hoffman & Flinchbaugh, 1982). A fixed-axis assumption can also be applied to elements rotating at varying angular velocities; this structure can be recovered from three projections of four elements sharing the same axis (Hoffman & Bennett, 1986).…”

Section: Discussionmentioning

confidence: 99%

Hierarchical motion organization in random dot configurations.

Bertamini¹,

Proffítt²

2000

Journal of Experimental Psychology: Human Perception and Perfor

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Motion organization has 2 aspects: the extraction of a (moving) frame of reference and the hierarchical organization of moving elements within the reference frame. Using a discrimination of relative motions task, the authors found large differences between different types of motion (translation, divergence, and rotation) in the degree to which each can serve as a moving frame of reference. Translation and divergence are superior to rotation. There are, however, situations in which rotation can serve as a reference frame. This is due to the presence of a second factor, structural invariants (Sis). Sis are spatial relationships persisting among the elements within a configuration such as a collinearity among points or one point coinciding with the center of rotation for another (invariant radius). The combined effect of these 2 factors-motion type and Sis-influences perceptual motion organization.An event is the natural unit of analysis for perception. An event is an actor or object that displays a behavior against a background, such as a falling object, the changing color of a traffic light, or the locomotion of an organism in the environment. In the case of motion, the background is the event's frame of reference, a coordinate system that may, itself, be moving. Because the motion of an element is defined relative to its reference frame, the element also shares the motion of the frame, and thus motion organizations are hierarchical.Hierarchical motion organizations are inherently ambiguous. Every motion affords an infinite number of different descriptions as a consequence of the choice of different moving coordinate systems, or frames of reference. Consider the motion of our planet. Common sense and medieval astronomy take the earth as the frame of reference for all motions: the flowing of a river; the locomotion of an animal; or the motion of the sun, moon, planets, and stars. Contemporary astronomy, on the other hand, takes the sun as a moving frame of reference. Within this reference frame, the earth is described as revolving around the sun, and the moon is described as having two kinds of motion, one around the earth and a second one, common to the earth, around the sun. This newer description of the solar system is no more true in a geometrical sense than the earth-centered one. From the point of view of providing an accurate description, any frame of reference is as good as any other. However, the use of the sun as a frame of reference for the earth and of the earth as a frame of reference for the moon promotes a better mechanistic description of this dynamical system.The perceptual system is adept at finding useful organizations for the motions that it encounters. When observing events, people correctly identify the motions of an object (where it is going) and motions within the object (what it is doing). The first are called common motions because they are common to the constellation of elements or features of the object. The second are called relative motions, implying that they are hierarchically orga...

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The interpretation of biological motion

Cited by 198 publications

References 3 publications

Tracking Individual Targets in High Density Crowd Scenes Analysis of a Video Recording in Hajj 2009

Tracking Individual Targets in High Density Crowd Scenes Analysis of a Video Recording in Hajj 2009

Minimum points and views for the recovery of three-dimensional structure.

Hierarchical motion organization in random dot configurations.

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