Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
  • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
  • G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
  • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
  • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
  • G06F3/014—Hand-worn input/output arrangements, e.g. data gloves
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
  • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
  • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
  • G06F3/033—Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor
  • G06F3/0346—Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
  • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
  • G06V40/20—Movements or behaviour, e.g. gesture recognition
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F2203/00—Indexing scheme relating to G06F3/00 - G06F3/048
  • G06F2203/033—Indexing scheme relating to G06F3/033
  • G06F2203/0331—Finger worn pointing device

Definitions

• the present invention relates to computer-based motion tracldng systems and particularly, though not exclusively, to a system capable of tracldng and identifying gestures or traj ectories made by a person.
• Gesture recognition systems have been identified in the art as being potentially valuable in this re -Oga"rd.
• WO 03/001340 describes a gesture recognition system which classifies gestures into one of two possible classes, namely (i) planar translation motion, and (ii) angular motion without translation. This enables separate gesture discriminators to work on the interpretation improving the chances of correct gesture discrimination.
• WO '340 proposes applying different classes of gestures to different functions, such as reciprocal actions for commands, tilt actions for positional (e.g. cursor) control and planar translational motions for handwriting.
• US 6681031 describes a gesture- controlled interface which uses recursive 'best fit' type operations attempting to find the best fit between all points on a projection of a sampled gesture to all points on candidate gestures.
• US 2204/0068409 describes a system for analysing gestures based on signals acquired from muscular activity.
• US 2004/0037463 describes a system for recognising symbols drawn by pen strokes on a sketch-based user interface by dividing the strokes into a number of sub-frames and deriving a signature for each sub-frame that is expressed as a vector quantity.
• US 6473690 describes a system for comparing and matching data represented as three-dimensional space curves, e.g. for checking geographic database accuracy.
• US 2004/0037467 describes a system for determining the presence of an object of interest from a template image in an acquired target image.
• a significant problem in gesture recognition S3 ⁇ stems is how to accurately, reliably and speedily detect a gesture or trajectory being made and compare it to a library of candidate gestures stored in a database.
• the present invention provides a gesture recognition method comprising the steps of: a) receiving input data related to a succession of positions, velocities, accelerations and/or orientations of at least one object, as a function of time, which input defines a trajectory of the at least one object; b) performing a vector analysis on the trajectory data to determine a number N of vectors making up the object trajectory, each vector having a length and a direction relative to a previous or subsequent vector or to an absolute reference frame, the vectors defining a gesture signature; c) on a vector by vector basis, comparing the object trajectory with a plurality of library gestures stored in a database, each library gesture also being defined by a succession of such vectors; and d) identifying a library gesture that corresponds with the trajectory of the at least one object.
• the present invention provides a gesture recognition engine comprising: an input for receiving input data related to a succession of positions, velocities, accelerations and/or orientations of at least one object, as a function of time, which input defines a trajectory of the at least one object; a gesture analysis process module for performing a vector analysis on the trajectory data to determine a number N of vectors making up the object trajectory, each vector having a length and a direction relative to a previous or subsequent vector or to an absolute reference frame, the vectors defining a gesture signature; and a gesture comparator module for comparing, on a vector by vector basis, the object trajectory with a plurality of library gestures stored in a database, each librae gesture also being defined by a succession of such vectors and identifying a library gesture that corresponds with the trajectory of the at least one object.
• Figure Ia is a perspective view of an exemplary motion tracking sensor arrangement
• Figure Ib is a perspective view of an alternative exemplary motion tracking sensor arrangement
• Figure 2 is a schematic diagram of a module for pre-processing accelerometer sensor outputs
• Figure 3 shows illustrations useful in explaining deployment of relative spherical coordinates in gesture definition, in winch figure 3 a shows a tracked gesture defined by absolute points in a Cartesian coordinate system and figure 3b shows the tracked gesture defined by points in a relative spherical coordinate system;
• Figure 4 is a schematic diagram of a gesture recognition system
• Figure 5 is a flowchart illustrating steps taken by a gesture analysis module during a gesture recognition process
• Figure 6 is a flowchart illustrating steps taken by a gesture comparator module during a gesture matching process.
• Figure 7 is a schematic diagram of a module for pre-processing accelerometer and angular rate sensor outputs.
• the expression 'gesture' is used to encompass a trajectory or motion behaviour of an object or of a selected part of an object in space.
• the object could, for example, be a person's hand, or an object being held in a person's hand.
• the object could be a person.
• the object may even be a part of a sensor device itself, e.g. a joystick control as guided by a user's hand.
• the trajectory which encompasses any motion behaviour, generally defines movement of an object or of part of an object relative to a selected stationary reference frame, relative to a moving reference frame, or even relative to another part of the object.
• a gesture may include a series of positions of the object or part of the object as a function of time, including the possibility that the object does not move over a period of time, which will generally be referred to as a 'posture' or 'stance.
• a posture or stance is to be included as a special case of a 'gesture', e.g. a fixed gesture.
• the expression 'object' used herein in connection with defining a gesture is intended to include part of a larger object.
• a wearable sensor 10 comprising an inertial sensor 11 is housed in a finger cap 12.
• the inertial sensor 11 is coupled, by wiring 13, to a processor (not shown in the drawing) contained in a strap assembly 14 that may be bound to the user's hand 15.
• the strap assembly 14 may also include a further inertial sensor (not shown) to provide position data of the user's hand relative to the finger, if desired.
• the strap assembly 14 preferably includes a telemetry system for streaming output data from the inertial sensor(s) to a computer system to be described.
• the telemetry system preferably communicates with the computer system over a wireless communication channel, although a wired link is also possible.
• the wearable sensor 10 preferably also includes one or more switches for signalling predetermined events by the user.
• a touch switch 16 may be incorporated into the finger cap 12 that is actuated by tapping the finger against another object, e.g. the thumb or desk.
• a thumb or finger operated function switch 17 may be located on or near the palm side of the strap assembly 14.
• the at least one inertial sensor 11 comprises three orthogonal linear accelerometers that determine rate of change of velocity as a function of time in three orthogonal directions as indicated by the straight arrows of figure Ia, together with three angular speed sensors that determine rotation rate about the three orthogonal axes, hi combination, these accelerometers and angular speed sensors are capable of providing information relating to the movement of the finger according to the six degrees of freedom.
• any sensor type and combination may be used that is capable of generating data relating to a succession of relative or absolute positions, velocities, accelerations and/or orientations of at least one object.
• a number of different types of such sensor are known in the art.
• FIG. 10 Another example of a sensor arrangement is now described in connection with figure Ib.
• This sensor arrangement may be described as a handheld sensor 10', rather than a wearable sensor as shown in figure Ia.
• the sensor 10' comprises an inertial sensor 11 ' is a housing 12' that may conveniently be held in one hand 15'.
• the inertial sensor 11 ' is coupled to a processor (not shown) contained within the housing 12'.
• a telemetry system communicates with a remote computer system 18 over a wireless communication channel, although a wired link is also possible.
• the sensor 10' preferably includes one or more switches 17' for signalling predetermined events by the user.
• touch switch 17' is incorporated into the housing 12' and is actuated by squeezing or applying pressure to the housing 12'.
• the at least one inertial sensor 11 ' comprises three orthogonal linear accelerometers that determine rate of change of velocity as a function of time in three orthogonal directions x, y, z.
• these accelerometers are capable of providing information relating to the movement of the object according to the three degrees of freedom. Roll and pitch can be deduced in relation to the earth's gravitational force, hence providing an additional two degrees of freedom for this embodiment.
• an object being tracked ma ⁇ ' include one or more markers identifying predetermined locations on the object that are to be tracked by suitable remote sensors.
• the markers may be optical, being remotely detectable by an imaging system or photocell arrangement.
• the markers ma ⁇ ' be active in the sense of emitting radiation to be detected by suitable passive sensors.
• the markers may be passive in the sense of reflecting radiation from a remote illumination source, which reflected radiation is then detected by suitable sensors.
• the radiation may be optical or may lie in another range of the electromagnetic spectrum. Similarly, the radiation may be acoustic.
• the object being tracked need not be provided with specific markers, but rely on inherent features (e.g. shape) of the object that can be identified and tracked b ⁇ ' a suitable tracking system.
• the object may have predetermined profile or profiles that are detectable by an imaging system in a field of view, such that the imaging system can determine the position and/or orientation of the object.
• any tracking system may be used that is capable of generating data relating to a succession of relative or absolute positions, velocities, accelerations and/or orientations of the object.
• a number of such tracking systems are available to the person skilled in the art.
• Figure 2 provides an overview of a data collection operation sensing motion of an object and pre-processing the data to obtain an acceleration signature that may be used by the gesture recognition system of the present invention.
• the outputs 22x, 22y, 22z from just three linear accelerometers 2Ox, 20 ⁇ ' and 2Oz are used.
• the linear accelerometers are preferably arranged in orthogonal dispositions to provide three axes of movement labelled x, y, and z. Movement of the object on which the accelerometers are positioned will induce acceleration forces on the accelerometers in addition to the earth gravitational field.
• the raw signals from the three orthogonal linear accelerometers are pre- processed in order to generate a set of data samples that can be used to identify gesture signatures.
• the outputs 22x, 22y, 22z of accelerometers 2Ox, 2Oy and 2Oz are preferably digitised using an appropriate A/D converter (not shown), if the outputs 22x, 22y, 22z therefrom are not already in digital form.
• the digitisation is effected at a sampling frequency and spatial resolution that is sufficient to ensure that the expected gestures can be resolved in time and space. More particularly, the sampling frequency is sufficiently high to enable accurate division of a gesture into a number N of portions or vectors as will be described later.
• the user marks the start of a gesture by activating a switch 21 (e.g. one of the possible switches 16, 17, 17' of figures Ia and Ib).
• This switch 21 could generally be in the form of a physical button, a light sensor or a flex sensor. More generally, manual activation of any type of electronic, electromechanical, optoelectronic or other physical switching device may be used.
• the user could mark the start of a gesture by means of another simple gesture, posture or stance that is readily detected by the s ⁇ f stem.
• the system ma ⁇ ' continuously monitor input data for a predetermined pattern or sequence that corresponds to a predetermined trajectory indicative of a 'start gesture' signal.
• the user could indicate the start of a gesture by any means of marking or referencing to a point in time to begin gesture recognition.
• the gesture recognition system could itself initiate a signal that indicates to the user that a time capture window has started in which the gesture should be made.
• Each of the three output signals 22x, 22y and 22z of the accelerometers 2Ox, 2Oy and 2Oz has a DC offset and a low frequency component comprising the sensor zero-g levels plus the offset generated by the earth's gravitational field, defined by the hand orientation.
• DC blockers 23x, 23y and 23z relocate the output signals around the zero acceleration mark.
• the resulting signals 26x, 26y, 26z are passed to low-pass filters 24x, 24y and 24z that smooth the signals for subsequent processing.
• the outputs 27x, 27y. 27z of filters 24x, 24y 5 24z are passed to respective integrators 28x. 28y 5 28z which can be started and reset by the switch 21.
• the output of this pre-processing stage comprises data 25 representing the trajectory or motional behaviour of the object, preferably in at least two dimensions.
• the start and end of the gesture, posture or stance may be indicated by operation of the switch 21.
• DC blockers 23 any or all of the functions of DC blockers 23.
• low-pass filters 24 and integrators 28 can be carried out in either the analogue domain or the digital domain depending upon the appropriate positioning of an analogue to digital converter.
• the accelerometers would provide analogue outputs 22 and the output data 25 would be digitised. Conversion may take place at a suitable point in the data path therebetween.
• the gesture recognition system operates on sequences of the two or three- dimensional values or samples gathered from the input devices as described above.
• the gesture defined by the motion behaviour curve or 'trajectory' of the object may describe a shape that has the same geometric structure as another gesture curve, yet appear unalike due to having a different orientation or position in space.
• the gesture recognition system preferably first converts the input 'Cartesian' value sequence to one of relative spherical coordinates. This form describes each gesture sequence independently of its macroscopic orientation in space.
• each three-dimensional value (x ⁇ , y n , Z 11 ) referenced against Cartesian axes 30 is described by a Cartesian three-tuple. Taken together as a sequence of position values they represent a gesture 31 - the path from (xj, y 1; zi) through to (X 4 , y 4 , Z 4 ). Translation, rotation or scaling of this shape will result in a new and different set of Cartesian values. However, for gesture comparison, it is desirable to make comparison of the input data for a tracked gesture at least partly independent of one or more of translation, rotation and scaling.
• a gesture is recognised even allowing for variation in the magnitude of the gesture (scaling), variation in position in space that the gesture is made (translation), and even the attitude of the gesture relative to a fixed reference frame (rotation). This is particularly important in recognising, for example, hand gestures made by different persons where there is considerable variation in size, shape, speed, orientation and other parameters between different persons' version of the same gesture and indeed between the same person's repetition of the same gesture.
• the azimuth angle ⁇ represents the angle between the vector pair in the plane defined by the vector pah"
• the zenith angle ⁇ represents the angle of that plane relative to the plane of the preceding vector pair.
• zenith angle 6 2 , 3 is the angle that the perpendicular of the V 2 , V 3 plane makes relative to the perpendicular of the V 1 , V 2 plane.
• the recognition process perceives the data as geometrical, and the data input values handled by the gesture recognition sj'stem may be absolute position in space, relative position in space, or any derivatives thereof with respect to time, e.g. velocity or acceleration.
• the data effectively define a gesture signature either in terms of a path traced in space, a velocity sequence or an acceleration sequence. In this manner, the process of the gesture recognition system can work effectively with many different types of sensor using the same basic algorithm.
• the gesture recognition system first performs pre-processing steps as discussed above in order to convert the input data into a useful data stream that can be manipulated to derive the values R, ⁇ and ⁇ above for any one of position, velocity or acceleration.
• the gesture recognition system 40 includes a module 41 for detecting or deterrnining the nature of the sensors 11 or 20 (figures 1 and 2) from which data is being received. This may be carried out explicitly by exchange of suitable data between the sensors 11 or 20 and the detection module 41. Alternatively, module 41 may be operative to determine sensor type implicitly from the nature of data being received.
• the detection module 41 controls a conversion module 42 that converts the input data using the pre-processing steps as discussed above, e.g. identification of start and end points of a gesture, removal of DC offsets, filtering to provide smoothing of the sensor output and analogue to digital conversion.
• a conversion module 42 that converts the input data using the pre-processing steps as discussed above, e.g. identification of start and end points of a gesture, removal of DC offsets, filtering to provide smoothing of the sensor output and analogue to digital conversion.
• a gesture recognition process receives (step 501) the input relating to a succession of positions, velocities or accelerations (or further derivatives) of the object as a function of time that define the gesture signature, or trajectory of the object being sensed.
• a gesture analysis process module 43 then performs steps to define the gesture signature in terms of the coordinate system described in connection with figure 3b. Firstly, a sampling rate r is selected (step 502). In a preferred embodiment, a default sampling rate is at least 60 samples per second, and more preferably 100 samples per second or higher. However, this may be varied either by the user, or automatically by the gesture analysis process module 43 according to a sensed length of gesture, speed of movement or sensor type.
• the process module 43 determines (step 503) whether analysis is to be carried out on the basis of position, velocity or acceleration input values, e.g. by reference to the determined sensor type.
• the process module 43 selects a number N of values to resample each gesture signature sequence into, i.e. the gesture signature is divided into TV " portions (step 504).
• the value for N " is 10.
• any suitable value may be used depending upon, for example, the length of gesture signature and the number of portions of gesture signatures in a library against which the input gesture signature must be matched.
• the JV portions preferably represent ⁇ ⁇ portions of equal temporal duration.
• the gesture signature is defined on the basis of JV equal time intervals or TV equal number of input data sample points.
• the N portions may be of equal length.
• the JV portions may be of unequal time and length, being divided by reference to points on the trajectory having predetermined criteria- such as points corresponding to where the trajectory has a curvature that exceeds a predetermined threshold.
• portions of the trajectory that have a low curvature may be of extended length, while portions of the trajectory that have high curvature may be of short length.
• Plural curvature thresholds may be used to determine portions of differing lengths.
• the process module 43 also determines the dimensional format of the data (step 505), i.e. how many dimensions the input values relate to. This also may affect the selection of candidates in a library of gesture signatures against which the input gesture signature may be potentially matched. For example, two or three dimensional samples may be taken depending upon sensor type, context etc.
• the N gesture signature portions are converted into N vectors V n hi the spherical coordinate sj'stem (step 506).
• the vectors V n are then normalised for each vector pair, to derive the ⁇ ectors in the relative spherical coordinate system described in connection with figure 4 (step 507). More specifically, R,,, ⁇ n and ⁇ ,, are determined where R,, is the ratio of the length of the 77.Hi vector to the preceding vector; ⁇ ,, is the angle between the nth vector and the preceding vector; and ⁇ , is the angle between the perpendicular of the plane defined by vectors ⁇ n, n-1 ⁇ and the perpendicular of the plane defined by the vectors ⁇ 77-1, n-2 ⁇ .
• the first vector will have a length and direction only.
• the direction of the first vector vi relative to a reference frame may be ignored if the gesture signature recognition is to be orientation insensitive.
• the direction of the first vector may be referenced against another frame, e.g. that of the object or other external reference.
• the direction of any vector in the sequence of N vectors may be used to reference against an external frame if absolute orientation is to be established.
• the first vector is selected for convenience, one or more vectors anywhere in the sequence may be used.
• the second vector will have an R value and a ⁇ value only, unless the plane of the first vector pair vi and V 2 is to be referenced against an external reference frame.
• the gesture signature has been defined as a sequence of R, ⁇ and ⁇ values for each of a plurality of portions or segments thereof (step 508).
• gesture recognition system 40 further includes a database or library 44 containing a number of gesture signatures, each gesture signature also being defined as a sequence of R, ⁇ and ⁇ values.
• the gesture signatures in the library will each have a type specification indicating a class of gestures to which they belong.
• the type specification may include a sensor type specification indicating the type of sensor from which the signature was derived, thereby indicating whether the signature specifies position data, velocity data or acceleration data.
• the type specification may also indicate a spatial dimension of the signature.
• the type specification may also indicate a size dimension of the signature, i.e. the number of portions (vectors) into which the signature is divided.
• Other type specifications may be included, providing a reference indicating how the library gesture signature should be compared to an input gesture or whether the library gesture signature is eligible for comparison with an input gesture.
• the gesture library 44 may be populated with gesture signatures using the gesture analysis module 43 when operating in a 'learn' mode. Thus, a user ma ⁇ ' teach the system a series of gesture signatures to be stored in the Library for comparison with later input gesture signatures. Alternatively or in addition, the library 44 may be populated with a collection of predetermined gesture signatures from another source.
• the gesture recognition system 40 further includes a gesture comparator module 45 for effecting a comparison of an input gesture signature with a plurality of previously stored library gesture signatures in the database library 44.
• the gesture comparator module 45 performs the following steps.
• a group or subset of library gesture signatures which are potentially eligible for matching with an input gesture signature is selected (step 601).
• the group may comprise one library of many libraries; a subset of the library 44; all available library gestures or some other selection.
• the group may be selected according to the type specification stored with each library gesture signature.
• a threshold for degree of match is determined (step 602).
• This may be a simple default parameter, e.g. 90%.
• the default parameter could be overruled by the user according to predetermined preferences.
• the default parameter could be selected by the system according to the gesture type specification. For example, three dimensional gesture signatures could have a different threshold than two dimensional gesture signatures, and acceleration signatures could have a different threshold than velocity signatures. Further, individual users may be provided with different threshold values to take into account a learned user variability.
• the threshold degree of match may be used by the gesture comparator module 45 to determine which library gestures to identify as successful matches against an input gesture signature.
• the gesture comparator module 45 may operate on a 'best match' basis, to determine the library gesture signature that best matches the input gesture signature.
• the threshold degree of match may then be used to provide a lower level cut-off below which library gestures will not even be regarded as potential matches and thus will not be considered for best match status.
• the next step carried out by the gesture comparator module 45 is to compare each of the N-I vector pairs of the input gesture signature with a corresponding vector ' pair of one of the group of library gestures selected for comparison, and to compute a difference value in respect of the length ratios (R,,), azimuth angles ( ⁇ ,,) and zenith angles ( ⁇ w ). These difference values are referred to respectively as dR n , d ⁇ n and d ⁇ n .
• the mean square error for each of the respective difference values for all portions of the signature is calculated, i.e. to find the mean square error for each of dR n , d ⁇ n and d ⁇ n in the signature comparison (step 604).
• This single error value may then be checked (step 606) to see if it is inside the threshold degree of match selected in step 602. If it is not, it can be discarded (step 607). If it is within the threshold degree of match, then the identity of the library gesture signature compared may be stored in a potential match list (step 608). The gesture comparator module 45 may then check to see if further library gesture signatures for comparison are still available (step 609), and if so, return to step 603 to repeat the comparison process with a new library gesture signature.
• the comparator module 45 may select the library gesture signature having the lowest error value from the potential match list.
• the comparator module 45 may alternatively present as a 'match' the first library gesture that meets the threshold degree of match criteria. Alternatively, the comparator 45 may output a list of potential matches including all gesture signatures that meet the threshold degree of match criteria. A number of other selection criteria will be apparent to those skilled in the art.
• the gesture comparator module 45 then outputs a list of potential matches, or outputs a single best match if the threshold degree of match criteria are met, or outputs a 'no match' signal if no library gestures reach the threshold degree of match criteria.
• the output module 46 may comprise a display output a printed output, or a control output for issuing an appropriate command or signal to another computer system or automated device to initiate a predetermined action based on the gesture identified by the match.
• the gesture recognition system 40 may be incorporated into another system to provide a user interface with that system, such that the system may be controlled at least in part by user gestures.
• gesture recognition system 40 perform gesture analysis based on a motion behaviour of a single 'track', e.g. the motion behaviour of a single point through or in space. It will be recognised that more complex object behaviour may also constitute a gesture signature, e.g. considering the motion behaviour of several points on the object in space, so that the gesture signature effectively comprises more than one 'track'. In another example, it may be desirable also to take into account rotational behaviour of a tracked point, i.e. rotation of the object about its own axes or centre of gravity.
• the sensor inputs may provide data for two or more tracked points on the object.
• these data may be considered as providing data for a 'compound signature', or signature having two or more tracks.
• Each of these tracked points may be analysed by the gesture analysis process module 43 in the manner already described.
• the gesture comparator module 45 may then average together the error values for each of the tracks in order to determine a final error value which can be used for the match criteria.
• multiple tracked points may be inferred from rotation data of the motion behaviour of the object if a sensor system that provided rotation behaviour is used.
• gesture signature recognition may be obtained by using signatures comprising two or more of position data, velocity data and acceleration data.
• the gesture analysis module 43 may separately determine R n , ⁇ ;? and O 7 , for position as a function of time, for velocity as a function of time and/or for acceleration as a function of time.
• the gesture comparator module 45 then separately compares positional R n , ⁇ ⁇ and ⁇ ,,, velocity R n , ⁇ ,, and O n and/or acceleration R n , ⁇ ⁇ and Q n of the gesture signature with corresponding values from the gesture library 44 in order to determine match.
• each of N vectors during gesture matching may be performed in respect of values of R, ⁇ and ⁇ for successive vectors, relative to a preceding vector. It is also possible to compare N vectors in respect of ⁇ and ⁇ values referenced to a fixed reference frame. For example, for a fixed reference frame having conventional Cartesian x, 3' and z axes, the values compared may be an azimuth angle ⁇ of the vector relative to the x axis within the x-y plane, and a zenith angle ⁇ of the vector relative to the z-axis (steps 507 and 508, figure 5).
• the ⁇ and ⁇ values of the 77th vector of the input gesture are compared with the corresponding ⁇ and ⁇ values of the 7?th vector of a library gesture, and similarly for all n from 1 to N " .
• the lengths / of the vectors are compared such that the length / of the /?th vector of the input gesture is compared with the length / of the corresponding ;?th vector of a library gesture, and similarly for all n from 1 to N.
• the comparisons may be on a difference basis or a ratio basis, e.g. and ⁇ ,, >mj3a/ / ⁇ , 7 ,/, ⁇ ,- ⁇ o . or ⁇ n ,mp ut ⁇ ⁇ njibrwy 3XiO. u n,mpui ' " n.hbrary Ol " n.mput ⁇ ⁇ " nj ⁇ rary-
• comparison step 603 is modified to include a transformation first applied to bring the input gesture signature vector data as close as possible to the current one of the library gestures being compared, the transformation being a combination of one or more of rotation, scale and translation. Then, in a modification to step 604, the root mean square error sum is calculated for all the N transformed input vectors compared to the respective N vectors of the library gesture signature. A zero error value would be a perfect match.
• the best transformation to apply may be determined according to any suitable method. One such method is that described by Berthold K P Horn in "Closed form solution of absolute orientation using unit quaternions", J. Opt. Soc. of America A, Vol. 4, p. 629 et seg, April 1987.
• Horn describes that the best translational offset is the difference between the centroid of the coordinates in one system and the rotated and scaled centroid of the coordinates in the other system.
• the best scale is equal to the ratio of the root-mean-square deviations of the coordinates in the two systems from their respective centroids.
• FIG 7 a further sensor arrangement and pre-processing module for providing velocity data input and positional data input is shown.
• Three orthogonal accelerometers 70 provide acceleration signals a x , a y , a 2 ; and three angular rate sensors 72 provide angular rotation rate signals ⁇ x , ⁇ y and ⁇ z .
• a switch or sensor 71 provides a gesture start / stop indication, similar to that described in connection with switch 21 of figure 2.
• the angular rate sensor data is passed to an attitude vector processing module 73 which determines a current attitude vector.
• TMs is used in conjunction with the three orthogonal acceleration signals a x . a y , a z to derive motion behaviour information for the six degrees of freedom by axis transformation module 74.
• This information is then processed by the integrator module 75 to derive velocity signals and position signals relative to a predetermined axis, e.g. the earth's gravitational field. These velocity and position signals may then be used as input to the gesture analysis process module 43.
• the gesture recognition system may also be provided with a calibration module.
• a user may be asked to perform certain specified gestures which are tracked by the sensors and analysed by the gesture analysis process module 43. These gestures are then added to the gesture library 44 for future comparison.
• the library gestures may include in their type specification, a user for which these gestures represent a valid subset for comparison.
• an output display may be provided to display a rendered image of the user's hand, or other object being tracked. This display may be overlaid with the gesture signature being tracked and/or identified.
• the system may be used to control that object.
• a handheld device such as a mobile telephone may be adapted to interface with the user by moving the mobile phone itself through predetermined gestures in order to instruct the phone to perform certain commands . , e.g. for menu access.
• a joystick may have the gesture recognition engine inbuilt to detect certain patterns of movement which can then be interpreted in a special way.
• the gesture recognition engine has many applications in computer gaming, e.g. for tracking the head, hand, limb or whole body movement of a game player to implement certain gaming input.

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• User Interface Of Digital Computer (AREA)
• Image Analysis (AREA)
• Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)

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Publications (1)

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Citations (5)

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• 2004
  • 2004-10-20 GB GB0423225A patent/GB2419433A/en not_active Withdrawn
• 2005
  • 2005-10-19 US US11/577,694 patent/US20080192005A1/en not_active Abandoned
  • 2005-10-19 EP EP05794750A patent/EP1810217B1/en not_active Not-in-force
  • 2005-10-19 DE DE602005009568T patent/DE602005009568D1/de not_active Expired - Fee Related
  • 2005-10-19 AT AT05794750T patent/ATE407409T1/de not_active IP Right Cessation
  • 2005-10-19 WO PCT/GB2005/004029 patent/WO2006043058A1/en active IP Right Grant

Patent Citations (5)

Non-Patent Citations (1)

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