Abstract:
The invention is directed to detecting a boundary position between a foot and a lower leg of a person in an image acquired by an imaging unit, the boundary position being a substantial boundary part, in a lower limb, between the foot, which is a part from a malleolus to a tip part, and the lower leg; detecting a feature quantity that makes it possible to classify a ground and a part other than the ground in the image; setting, in a peripheral region around the boundary position, a plurality of local regions having positional information and/or direction information relative to the boundary position, and determining whether each of the local regions is the ground or the part other than the ground by using the feature quantity unique to the ground; determining a foot region from the local region determined as the part other than the ground; and estimating a direction of the foot of the person from the local region classified as the foot region and from the information.

Description:
TECHNICAL FIELD 
       [0001]    The present invention relates to a method for estimating a direction of a person standing still. 
       BACKGROUND ART 
       [0002]    It is necessary for an autonomous mobile apparatus to determine a moving direction of a person in order to move forward safely and effectively. 
         [0003]    As a background art in the present technical field, there is JP 2007-229816 A (PTL 1). In PTL 1, a method for predicting a course of a pedestrian from a toe image is described. In the method, a pedestrian course model construction unit constructs a course model of a general pedestrian in advance by combining information of a toe image of a specific pedestrian and detected course information of the specific pedestrian, and a pedestrian course model storage unit stores information of the pedestrian course model. 
         [0004]    Then, a pedestrian course prediction unit predicts a course of an unspecific pedestrian by collating information of a toe image of the unspecific pedestrian, which image is generated by a pedestrian toe image generation unit, and the information of a pedestrian course model stored in the pedestrian course model storage unit. 
         [0005]    As a method to detect a course in construction of a pedestrian course model, it is described to detect a three-dimensional position of a pedestrian serially in certain time intervals and to detect the course of the pedestrian from a temporally change of the three-dimensional position. 
       CITATION LIST 
     Patent Literature 
       [0006]    PTL 1: JP 2007-229816 A 
       SUMMARY OF INVENTION 
     Technical Problem 
       [0007]    In PTL 1, a pedestrian course model is constructed from a positional change of a pedestrian in predetermined time intervals. However, there is no positional change in a person who stands still (person standing still), and thus, it is not possible to construct a course model and to estimate a direction. Also, by a method of performing pattern matching with a database which is like a general pedestrian model of PTL 1, it is not possible to estimate a direction when appearance, such as clothes, a physique, or the like, of a person standing still is greatly different from that of a person in the database. 
         [0008]    However, in a case where an autonomous mobile apparatus such as a robot passes through an environment crowded with people standing still, it is necessary to estimate a direction in which a person standing still starts walking, in order to prevent the autonomous mobile apparatus from hitting the person or blocking movement of the person even when the person standing still suddenly starts walking. A direction in which a person standing still starts walking often matches a direction of a foot. The person standing still starts to move to a side or a backward of the foot for only about one or two steps. Thus, it is suitable to detect a direction in which a person starts to move by a direction of a foot. 
         [0009]    A purpose of the present invention is to provide a method for estimating a direction of a person standing still, which method makes it possible to perform a safe movement control by estimating a direction, in which a person standing still starts to walk, from a momentary single still image of the person standing still and by moving through a region in which the person is not likely to be hit. 
       Solution to Problem 
       [0010]    To achieve the above purpose, the present invention includes the steps of: detecting a boundary position between a foot and a lower leg of a person in an image acquired by an imaging unit, the boundary position being a substantial boundary part in a lower limb between the foot, which is a part from a malleolus to a tip part, and the lower leg; detecting a feature quantity which makes it possible to classify a ground and a part other than the ground in the image; setting, in a peripheral region around the boundary position, a plurality of local regions having positional information and/or direction information relative to the boundary position, and determining whether each of the local regions is the ground or the part other than the ground by using the feature quantity unique to the ground; determining a foot region from the local region determined as the part other than the ground; and estimating a direction of the foot of the person from the local region classified as the foot region and from the information. 
         [0011]    Also, to achieve the above purpose, preferably in the present invention, the boundary position between the foot and the lower leg is specified by using a distance sensor. 
         [0012]    Also, to achieve the above purpose, preferably in the present invention, the distance sensor is parallel to the ground and measures a plane surface at a height of the substantial boundary part, in the lower limb of the person, between the foot and the lower leg. 
         [0013]    Also, to achieve the above purpose, preferably in the present invention, the feature quantity of the ground is calculated based on a histogram of data in each pixel in the image. 
         [0014]    Also, to achieve the above purpose, preferably in the present invention, each of the local regions, which is set in the peripheral region around the boundary position between the foot and the lower leg, is a sector with the boundary position as a center. 
         [0015]    Also, to achieve the above purpose, preferably in the present invention, when a distance between paired foot regions is smaller than a predetermined value and a difference in a feature quantity between the paired foot regions is equal to or smaller than a predetermined value, the paired foot regions are determined as the foot regions of the same person. 
         [0016]    Also, to achieve the above purpose, preferably in the present invention, a direction of the person is estimated based on the information held in the local region which is included in the foot region of the same person. 
       Advantageous Effects of Invention 
       [0017]    According to the present invention, it is possible to provide a method for estimating a direction of a person standing still, which method makes it possible to perform a safe movement control by estimating a direction, in which a person standing still starts to walk, from a momentary single still image of the person standing still and by moving through a region in which the person is not likely to be hit. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0018]      FIG. 1  is a flowchart for describing a step of estimating a direction according to an embodiment of the present invention. 
           [0019]      FIG. 2  is a schematic configuration view illustrating a direction estimating apparatus according to the embodiment of the present invention. 
           [0020]      FIGS. 3(   a ) to  3 ( c ) are schematic appearance views illustrating the direction estimating apparatus according to the embodiment of the present invention. 
           [0021]      FIG. 4  is a flowchart for describing a method for estimating a foot-lower leg boundary position according to the embodiment of the present invention. 
           [0022]      FIG. 5  is a view for describing a method for estimating a horizontal plane foot-lower leg boundary position according to the embodiment of the present invention. 
           [0023]      FIG. 6  is a view for describing an example of a method for calculating projection according to the embodiment of the present invention. 
           [0024]    FIGS.  7 ( 1 ) and  7 ( 2 ) are views for describing an estimation result of the foot-lower leg boundary position according to the embodiment of the present invention. 
           [0025]    FIG.  8 ( 1 ) is a view and FIG.  8 ( 2 ) is a chart, which are for describing a method for extracting a feature quantity of a ground according to the embodiment of the present invention. 
           [0026]    FIGS.  9 ( 1 ) to  9 ( 4 ) are views for describing a method for estimating a foot direction of a person according to the embodiment of the present invention. 
           [0027]      FIG. 10  is a view for describing a local region according to the embodiment of the present invention. 
           [0028]      FIG. 11  is a flowchart for describing processing for specifying a tiptoe region in the embodiment of the present invention. 
           [0029]      FIG. 12  is a configuration view illustrating a direction estimating apparatus according to a different embodiment of the present invention. 
           [0030]      FIGS. 13(   a ) and  13 ( b ) are appearance views illustrating the direction estimating apparatus according to the different embodiment of the present invention. 
       
    
    
     DESCRIPTION OF EMBODIMENTS 
       [0031]    In the following, embodiments will be described with reference to the drawings. 
       First Embodiment 
       [0032]      FIG. 2  is a view illustrating a configuration example of a direction estimating apparatus  1  in which the present embodiment is mounted. 
         [0033]      FIGS. 3(   a ) to  3 ( c ) are appearance views of the direction estimating apparatus  1 . 
         [0034]    In  FIG. 2 , the direction estimating apparatus  1  includes a digital camera  101 , a laser scanner  102 , a calculator  103 , and an output terminal  104 . The digital camera  101  acquires a digital image G and transmits the acquired digital image G to the calculator  103 . The laser scanner  102  transmits a measurement value to the calculator  103 . The calculator  103  estimates a direction of a person  201  based on information acquired from the digital camera  101  and the laser scanner  102 , and outputs a result as an electric signal to the output terminal  104 . 
         [0035]    In  FIGS. 3(   a ) to  3 ( c ), the digital camera  101  is provided to an upper part of a direction estimating apparatus  2 . As illustrated in  FIG. 3(   b ), the digital camera  105  is attached in an inclined manner to photograph, from above, an object to be photographed. The laser scanner  102  is provided to a lower part of the direction estimating apparatus  1 . The calculator  103  is placed around a central part of the direction estimating apparatus  2  and connected to the output terminal  104  behind the calculator  103 . 
         [0036]    With reference to the flowchart in  FIG. 1 , a method for estimating a direction of a person standing still according to the present embodiment will be described. 
         [0037]    In S 1  in  FIG. 1 , a digital image G around a foot of the person  201  is acquired from the digital camera  101 . Each pixel in the digital image G includes, as numerical data C, color information such as RGB intensity. By using an infrared camera, a stereo camera, a three-dimensional distance sensor, or the like as an imaging unit, temperature information, distance information, or the like can be suitably used. In the present embodiment, the RGB intensity is used as the numerical data C. 
         [0038]    In S 2 , a position indicating a boundary part between a foot and a lower leg (foot-lower leg boundary position O M ), in the image G, of a person standing still in the image G is set. Processing in S 2  is illustrated in a flowchart in  FIG. 4 . 
         [0039]    In SS 101 , the laser scanner  102  scans a plane surface F 302  parallel to a ground T 301 , which is illustrated in  FIG. 3(   c ), and a coordinate data group of a surface of the boundary part between the foot and the lower leg of the person  201  is acquired. 
         [0040]    As illustrated in  FIG. 3(   c ), the height of the plane surface F 302  is around 15 to 30 cm, and the height around an ankle of a person is suitable thereto. In SS 102 , a representative position of a cross sectional surface of the boundary between the foot and the lower leg on the plane surface F 302  (horizontal plane foot-lower leg boundary position O′ M ) is set from the coordinate data group acquired in SS 101 . As a method for the setting, there is a following method. 
         [0041]    First, in the coordinate data group acquired by the laser scanner  102 , coordinate data points are separated into groups by regarding adjacent coordinate data points within a range of a certain distance as coordinate data points of the same object. Then, as illustrated in  FIG. 5 , in a case where a shape of the cross sectional surface of the boundary between the foot and the lower leg is regarded as a circle, a central position of the cross sectional surface of the boundary is set as the horizontal plane foot-lower leg boundary position O′ M . 
         [0042]    For example, in a case where a coordinate data point group which belongs to a group k includes {d 1 , d 2 , d 3 , and d 4 }, three coordinate data points {d i , d j , and d k } (i, j, and k are arbitrary natural numbers) are selected arbitrarily, and an intersection of perpendicular bisectors, each of which is formed by arbitrary two points among {d i , d j , and d k }, is set as the horizontal plane foot-lower leg boundary position O′ M . In SS 103  in  FIG. 4 , the horizontal plane foot-lower leg boundary position O′ M  acquired in SS 102  is projectively transformed, and the foot-lower leg boundary position O M  in the digital image G acquired in S 1  is calculated. 
         [0043]    As illustrated in  FIG. 6 , when an imaging surface of a camera is regarded as a plane surface M 303 , an arbitrary point X (x, y) on the plane surface F 302  can be projectively transformed into a point X′ (x′, y′) on the plane surface M 303  which satisfy an equation 1. 
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         [0044]    By determining real coefficients a 0 , b 0 , c 0 , a 1 , b 1 , c 1 , a 2 , b 2 , and c 2 , a mapping relationship between the plane surface F 302  and the plane surface M 303  is derived. By reducing a denominator and a numerator on the right-hand side, it can be regarded that the equation 1 includes eight independent variables. 
         [0045]    Thus, by measuring four vertexes of a tetragon A′B′C′D′, which is a rectangle ABCD on the plane surface F 302  imaged onto the plane surface M 303  as illustrated in  FIG. 6 , coordinates of four vertexes of the rectangle ABCD being already known, and by solving simultaneous equations by substituting a coordinate of each of the vertexes ABCD and A′B′C′D′ into the equation 1, all coefficients can be calculated. By calculating a coefficient before activating an apparatus, projective transformation of an arbitrary point on the plane surface F 302  onto the plane surface M 303  is calculated. Thus, as illustrated in FIGS.  7 ( 1 ) and  7 ( 2 ), it is possible to projectively transform the horizontal plane foot-lower leg boundary position O′ M  calculated in SS 102 , and to calculate the foot-lower leg boundary position O M  in the digital image G. 
         [0046]    In S 3  in  FIG. 1 , a feature quantity Q f  unique to a ground is extracted from the digital image G. A method for extracting the feature quantity will be described with reference to FIGS.  8 ( 1 ) and  8 ( 2 ). 
         [0000]    Each pixel in the digital image G in FIG.  8 ( 1 ) includes RGB intensity as a numerical value. When calculated, a histogram of the RGB intensity of the digital image G resembles FIG.  8 ( 2 ). Since the ground occupies a great part of the digital image G, a color in the vicinity of each of the peaks R m , G m , and B m  of RGB in the histogram in FIG.  8 ( 2 ), is estimated as a color of the ground, and RGB intensity which satisfies an equation 2 is set as the feature quantity Q f  unique to the ground. 
         [0000]      [Mathematical Formula 2] 
         [0000]    
       
      
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         [0000]      ∩ G   m   −ΔG   f   &lt;G&lt;G   m   +ΔG   f  
 
         [0000]      ∩ B   m   −ΔB   f   &lt;B&lt;B   m   +ΔB   f }  equation 2
 
         [0047]    ΔR l , ΔR r , ΔG l , ΔG r , ΔB l , and ΔB r  are arbitrary real numbers and are set suitably according to a condition of the ground. Note that when Q f  is constant all the time, Q f  may be extracted in advance and may be stored inside or outside the apparatus. 
         [0048]    In S 4  in  FIG. 1 , a local region D k  is set in order to find a region including a foot (foot region) from a peripheral region of the foot (foot peripheral region E) in the digital image G. For example, as illustrated in FIG.  9 ( 2 ), it is assumed that foot-lower leg boundary positions O MR  and O ML  in right and left lower limbs are set by S 2 . First, the digital image G is projectively transformed, in a similar manner to S 2 , onto a surface parallel to the ground, and a state of the foot viewed from a vertical direction toward the ground is simulated. Here, projectively transformed image is regarded as G′, and projection positions of O MR  and O ML  are regarded as O″ MR  and O″ ML , respectively. Next, a region, which is sandwiched between a circle having a radius of r min  and a circle having a radius of r max  with a foot-lower leg boundary position O″ MR  or O″ ML  after the projective transformation as a center, is regarded as the foot peripheral region E. Then, from the foot peripheral region E, a plurality of local regions D k  is selected. Each of the local regions D k  is set to include information of a position or a direction. 
         [0049]    In the present embodiment, as illustrated in  FIG. 10  and expressed in an equation 3, D k  is set according to an arbitrary direction e, with O″ M  as a center. 
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         [0050]    r min , r max , Δθ, and the number of D k  are set suitably according to an environment. 
         [0051]    In S 5  in  FIG. 1 , each of the local regions D k  is evaluated and determined whether it is the ground. Among the pixels in each of the local regions D x , the number of pixels which satisfy a condition of the feature quantity Q f  is regarded as an evaluation value of the local region D k . It can be determined that the higher the evaluation value is, the more ground the region has. When the evaluation value is larger than a predetermined value, D k  is determined as the ground. When the evaluation value is smaller than a predetermined place, D k  is determined as a part of the foot, and a step goes to S 6  and D k  is classified as a foot region K {D q } (q is natural number). Note that in the present embodiment, the foot peripheral region E is regarded as a circle, and the local region D is regarded as a sector. However, a polygon, an ellipse, or the like can be selected suitably. 
         [0052]    In S 7  in  FIG. 1 , it is checked whether all D, is evaluated. When there is a local region D k  which is not evaluated yet, a step goes back to S 4  and D k  which is not evaluated yet is evaluated. 
         [0053]    In S 8  in  FIG. 1 , a foot direction e 8  of an object M is estimated from a positional relationship between the local region D q  classified as the foot region K and the foot-lower leg boundary position O M . 
         [0054]    For example, in a case of FIG.  9 ( 3 ), at a time point of S 8 , D p  (p=1, 2, 3 . . . , 6) and D. are classified as the foot region K. D p  is a region including a tiptoe (tiptoe region T), and D. is a region including a lower leg (lower leg region L). A foot direction of a person is a direction of a tiptoe with the foot-lower leg boundary position O N  as a basis, and thus, it is possible to identify a foot direction from a position of the tiptoe region T. An example of separation of the tiptoe region T and the lower leg region L will be described with reference to a flowchart in  FIG. 11 . 
         [0055]    In SS 201 , grouping is performed and local regions D q , which belong to the foot region K and are continuously adjacent, are separated into the same group. In SS 202 , the number of groups is checked, and when there are two or more groups, a step goes to SS 203 . A group in a direction close to a front direction (−y direction in FIG.  9 ( 3 )) is determined as the tiptoe region T. When there is only one group, a step goes to SS 204 , and the group is determined as the tiptoe region T. In SS 205 , an average value in a direction θ p  which sets the local region D p  included in the tiptoe region T is regarded as the foot direction θ M . 
         [0056]    For example, in a case of FIG.  9 ( 4 ), a direction which sets a local region D Ln  having the foot-lower leg boundary position O″ ML  as a basis is regarded as θ Ln , and an average value in θ Ln  is regarded as a foot direction θ ML  on O″ ML . A foot direction θ MR  on the foot-lower leg boundary position O″ MR  is calculated in a similar manner. 
         [0057]    All the foot directions estimated in such a manner are output from the output terminal  104 . Also, in S 8 , when a distance between O″ ML  and O″ MR  is smaller than a certain value L and predetermined feature quantities Q M  of the tiptoe regions D Ln  and D Rn , which respectively have O″ MR  and O″ ML  as centers, are close to each other, the tiptoe regions D Ln  and D Rn  are determined as those of the same person and the average value in θ ML  and θ MR  may be estimated as the foot direction θ M  of the person  201 . As the feature quantity Q M , a feature point coordinate or the like by an RGB color histogram or edge processing is used suitably. Thus, even when the image G includes a plurality of people, it is possible to estimate a direction of each person independently. 
         [0058]    In such a manner above, it becomes possible to estimate a foot direction of the person  201  from a single image without using a database. 
       Second Embodiment 
       [0059]    In the present embodiment, an example of using a distance image will be described. 
         [0000]    In  FIG. 12 , a direction estimating apparatus  2  for a person standing still according to the second embodiment is illustrated. In  FIGS. 13(   a ) and  13 ( b ), appearance views of the direction estimating apparatus  2  are illustrated. 
         [0060]    In the direction estimating apparatus  2  in  FIG. 12 , description of a part having the same function with the configuration having the same assigned signs and are illustrated in  FIG. 2  and  FIG. 3  which have been already described is omitted. 
         [0000]    The direction estimating apparatus  2  illustrated in  FIG. 12  includes a stereo camera  105  as an imaging unit, and two digital images in which an object to be photographed is viewed from different positions are transmitted to a calculator  103 . The calculator  103  calculates a distance, with a ground T 301  as a basis, of an object in the images from the two digital images, and generates a distance image G 3D . Then, the calculator  103  estimates a direction of a person  201  by using distance information as numerical data C included in each pixel. 
         [0061]    In  FIGS. 13(   a ) and  13 ( b ), the stereo camera  105  is provided to an upper part of the direction estimating apparatus  2  and photographs a stereo image with two lenses. As illustrated in  FIG. 13(   b ), the stereo camera  105  is attached in an inclined manner to photograph, from above, an object to be photographed. The calculator  103  is placed around a central part of the direction estimating apparatus  2  and connected to the output terminal  104  behind the calculator  103 . 
         [0062]    A flow of processing in the second embodiment will be described with reference to the flowchart in  FIG. 1 . However, S 4  to S 8  are the same with S 4  to S 8  of the first embodiment which has been described already, and thus, description thereof is omitted. 
         [0063]    In S 1 , two digital images G 1  and G 2  are acquired from a stereo camera  104 . 
         [0000]    In S 2 , the distance image G 3D  is generated from the digital images G 1  and G 2 . The generation of the distance image G 3D  is performed, for example, by the following method. First, edge extraction or the like is performed on a minute region a 1n  in the digital image G 1 , and a feature quantity s 1n  is given thereto. Next, a minute region a 2n  having a feature quantity s 2n  which is the same with the feature quantity s 1n  of a 1n  is searched from G 2 . Then, a distance z, to a minute region a kn  (k=1, 2) is calculated by an equation 4, and is regarded as a distance of a minim region a 1n . 
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         [0064]    Here, g kn  (k=1, 2) is a barycentric position of a kn , f is a focal distance of a camera, and h is a space between two cameras. By performing the calculation on the whole digital image G 1 , the distance image G′ 3D  from the camera can be obtained. The distance image G 3D  with the ground T 301  basis can be easily acquired from G′ 3D . 
         [0065]    In S 3 , a foot-lower leg boundary position is specified. In the distance image G 3D  acquired in S 2 , a pixel, in which a distance C is larger than the height from the ground T 301  to an ankle of a person and the distance C is smaller than a predetermined height, is recognized as the foot-lower leg boundary position of the person  201 , whereby a foot-lower leg boundary position in the image G 1  or G 2  can be specified immediately. 
         [0066]    In S 4 , a feature quantity Q f  of the ground is extracted. The feature quantity Q: of the ground indicates that a distance is in the vicinity of zero and is expressed in an equation 5. 
         [0000]      [Mathematical Formula 5] 
         [0000]        C   f   ={C∥C|&lt;ε}   equation 5
 
         [0067]    ε is an arbitrary real number and is set suitably according to a condition of the ground. After S 4 , processing similar to that of the first embodiment is performed on the image G 1  or G 2 , and thus, a foot direction of a person can be estimated. 
       Third Embodiment 
       [0068]    In the first embodiment, when a plurality of colors is included in the ground, there is a plurality of peaks in the histogram. In such a case, a color in the vicinity of each peak may be regarded as the feature quantity of the ground. 
       Fourth Embodiment 
       [0069]    In the first, second, and third embodiments, in a case where the feature quantity of the ground varies depending on a position of each person, it is possible to correspond to the case by acquiring a feature quantity of a region not including a foot of each person from a local image around the foot of each person. 
       REFERENCE SIGNS LIST 
       [0000]    
       
           1  direction estimating apparatus of first embodiment 
           2  direction estimating apparatus of second embodiment 
           101  digital camera 
           102  laser scanner 
           103  calculator 
           104  output terminal 
           105  stereo camera 
           201  object person 
         T 301  ground on which object person actually stands 
         F 302  scan surface of laser scanner 
         M 303  imaging surface of digital camera 
         G digital image 
         C feature quantity of image 
         Q f  feature quantity of foot contact surface 
         O M  foot-lower leg boundary position of person 
         D local region 
         E foot peripheral region 
         K foot region 
         θ direction