The Detection of Obstacles Using Features by the Horizon View Camera


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1 The Detection of Obstacles Using Featues b the Hoizon View Camea Aami Iwata, Kunihito Kato, Kazuhiko Yamamoto Depatment of Infomation Science, Facult of Engineeing, Gifu Univesit Abstact In this pape, we popose a new camea sstem called Hoizon View Camea (HVC). The HVC is a sstem in which the optical ais of a camea is diected at the hoizon with a mio so that obtained image contains objects on the gound without including the gound itself. Theefoe, b using the HVC sstem, sepaating objects fom the gound becomes ve eas. In this pape, we measued the distance to the object b using the obtained image actuall and easil. Moeove, thee ae man othe useful featues in the HVC sstem. In ode to impove the pocessing cost and accuac, we popose a new idea wheeb the detection of objects becomes easie and the esults ae moe accuate b the epeiment. 1 Intoduction Nowadas, man eseaches of autonomous obots has been poposed. Accoding to eseaches, the visual infomation fom a camea is useful fo an autonomous obot because the autonomous obot has to ecognize suounding scene using the visual infomation [1]. Fo eample, when the obot moves, the obot has to ecognize objects such as obstacles that limit action. In methods of detecting objects, a single camea o a steeo camea is usuall used. Howeve, these methods have some poblems. In the case of using the steeo camea, two o moe cameas ae needed which inceases the cost. Also the pocessing tends to compleif [2][3]. On the othe hand, in the case of using the single camea, while cost becomes low because onl one camea is needed, it is necessa to keep the camea at a highe position in ode to acquie highe accuac [4]. Theefoe, the height of the sstem becomes inevitabilit tall. So, we popose a new camea sstem called the Hoizon View Camea (HVC) fo constucting a small size obot [5]. 2 HVC Sstem 2.1 Outline of the HVC Sstem In the case of using a single camea, it is necessa to keep the camea at a highe position in ode to acquie highe accuac, but this stateg has the poblem that the sstem becomes tall. To emed this, we came acoss a diffeent viewpoint to this method. Ou new idea is to keeping the camea at a low position, i.e., the camea is put on the gound. B this method, the obtained image contains onl suounding objects without the gound because the sstem position is too low. Fo this pape, theefoe, the camea was put on the gound, and the sstem was made so that the optical ais of the camea was diected to the hoizon. This sstem is named the Hoizon View Camea (HVC). The obtained image b the HVC sstem contains objects on the gound without including the gound itself. Theefoe, the HVC sstem has advantages that sepaating objects fom the gound becomes ve eas, and the calculation time fo that can be educed. B moving fowad, the HVC sstem can easil measue the distance to an object. We tied to make the HVC sstem, but we have to bu half of the camea in the gound to make the optical ais of the camea diect to the hoizon, an impossibilit in actual Camea 2θ θ Cente of optical ais Mio Figue 1: HVC sstem
2 applications. Theefoe, the optical ais of a camea was diected to the hoizon b using a mio. The HVC sstem is shown in figue 1. The image obtained b this sstem is sepaated hoizontall into two pats; the uppe half of the image is the image eflected b the mio, and the lowe half of the image is the diect image in font of the sstem. An eample is shown in figue 2, and figue 3 shows a sequence of a peson walking font of the HVC of an animation which was ecoded b the HVC. 2.2 Featue of the HVC Sstem In this sstem, eve object in the image is consideed an obstacle, because the gound is not included in the uppe half of the image. Theefoe, the distance to the object is measued with the eflected image onl b moving the HVC, without detection of the object. The images obtained b the HVC sstem have a featue that its emission point of the optical flow which is fomed b the movement of the sstem is located on the hoizon of the image. Moeove, when the HVC sstem moves fowad, the emission point eists at the cente of the hoizon. The optical flow of a standstill object flows adiall fom the emission point to outside. Figue 4 shows the optical flow of the HVC sstem. If the optical flow does not flow fom the emission point, that pat of the image can be ecognized as a moving object. The geneal sstems of the single camea with a mio ae poposed. These sstems ae intended to obtain steeo images b the single camea eclusivel [6]. But in the case of the HVC sstem using the mio, this sstem is not intended to obtain steeo images b the single camea as usual although two kinds of the obtained image. The HVC sstem is intended to be able to detect objects of the font of this sstem easil based on the new idea. Moeove, when the HVC sstem moves fowad, this sstem can measue the distance to objects using one kind of the obtained image. The HVC also has a featue that the image of the object in the cente of the optical ais does not move when the HVC moves fowad. Image b eflection of the mio Hoizon Diect image in font of the sstem Emission point Figue 2: Obtained image of the HVC (32 24 piels) Figue 4: Optical flow of the HVC Figue 3: The animation fom the HVC
3 3 Measuing the Distance to Objects We used the optical flow fo measuing the distance to an object in the image [7]. When the camea is moved fowad, objects close to the camea move moe than those fathe awa in the image. Moeove, the distance of the movement also diffes b the distance between the object and the cente of the optical ais. If the object is located fa fom the cente of the optical ais, it moves moe than if the object is located nea the cente of the optical ais. B using this diffeence, the movement vecto of the object in the image befoe and afte the camea's movement can be calculated. The distance can then be measued b the diection and the size of each movement vecto to the object. Fo this pape, we used template matching to detect the optical flow [8]. So, the distance to the object is measued b the optical flow. The distance to the object is calculated b the tiangulation, because the angle fom the camea to each piel of the image is constant, and the distance of the camea movement is known. To measue the distance fom the camea to the object, we have to know the camea paamete, the angle coesponding to each piel. The calculation fo the camea used hee is pesented. In the place of locating S fom the camea, the image was h high b w wide as shown in figue 5. The value of θ that is the angle of each piel fom the camea is decided b using these values. J P(I, J) p(, ) I θ Scm Image Real coodinates Figue 6: The angle of each piel I J tan θ = (2) S Figue 7 shows the method of calculating the distance. The value of θ 1, θ 2 fo each piel and d ae known. Using the value of θ 1, θ 2 calculated fo each piel, the distance to the object is calculated b eq.(3), whee d is the distance the camea moved, and D is the distance to the object. θ 2 θ 1 Camea movement Cente of image Hoizon h w D Figue 7: Measuement of the distance to the d Image fom camea S d tan θ tan θ tan θ 1 D = (3) Impovement of the Distance Measuing Figue 5: Camea paametes In the case of a esolution of W H piels, p(, ) is calculated b eq.(1) to give P(I, J), since the cente of the hoizon is at the oigin, W w H P ( I, J ) = p(( ), ( ) 2 W 2 (=~W, =~H/2) The obtained P(I, J) is an actual position S fom the camea. Figue 6 shows how to calculate the angle of each piel in the image. Theefoe, the angle of each piel fom the camea is calculated b eq.(2). h H ) (1) In ode to impove the computation cost and accuac, a new idea was intoduced using the popet of HVC sstem. When an uppe image fom the HVC was tansfomed to the logpola coodinates [9][1], the popet appeas with eas and effective image pocession. As noted peviousl, when the HVC sstem moves fowad, the optical flow flows fom the cente of the hoizon. So tansfomed image to the logpola coodinates, the optical flow flows upwad. Using this popet, we think that the optical flow can be detected moe coectl and the accuac of the distance calculation can be impoved. Also, if the optical flow does not flow upwad, the object of that image can be ecognized as a moving object like the optical flow of the oiginal image. Figue 8
4 shows the tansfomation to the logpola coodinate. Also we tansfom to its logpola countepat b eq.(4). B using geneal equation of the logpola tansfom, objects distant fom the cente of the hoizon ae tansfomed to a small size. Theefoe, when we detect the optical flow, the accuac of the distance measued becomes low because the size of each vecto is small. Theefoe, in this pape, we decided eq.(4) in which the inceasing ate of log is egulated b using the value of k to detect the optical flow to be able to measue the distance with enough accuac. Figue 9 shows the uppe of the obtained image b the HVC sstem (XY image), and the tansfomed image to the coesponding logpola coodinate (logpola image). In the logpola image, the optical flow of standing objects constantl flows upwad. B using this popet, a pocess of detecting the optical flow becomes ve eas, because the seaching aea fo the template matching is limited to a small aea, and the computation cost is educed. Figue 1 shows the optical flow of the XY image and the logpola image. Also in the XY image as shown figue 9 (a), objects ae moving to the outside fom the cente of the hoizon. In the logpola image as shown figue 9 (b), objects ae moving to upwad. Tansfom π π Figue 8: Tansfom to the logpola coodinate = log = tan e 2 2 { k + + 1} 1 (4) Fame 1 Fame 2 Fame 3 Fame 4 Fame 5 Fame 6 (a) XY image Fame 1 Fame 2 Fame 3 Fame 4 Fame 5 Fame 6 (b) logpola image Figue 9: Tansfom to the logpola image
5 XY image Tansfom Figue 1: Optical flow of XY image and logpola image π/2 logpola image π Moeove, b using the logpola image, we think that optical flow can be detected moe coectl and the accuac of the distance calculation can be impoved. Because the featue of an object with staight lines o tetues which ma cause failue in the template matching is changed into comple featue, the template matching becomes easie. In ode to decide the distance, we substituted eq.(4) into eq.(1) to obtain P(I, J), and we calculated b substituting the obtained P(I, J) in eq.(2). We obtained the distance to the object D b substituting the angle of each piel in eq.(3). We can also measue the distance to the object in the logpola image b eq.(5). In eq.(5), q( 1, 1 ) and q ( 2, 2 ) ae coodinate values of the object in the logpola image befoe and afte movement espectivel as shown in figue 11. In the logpola image, 1 and 2 ae constant if the HVC moves fowad, because the optical flow flows upwad diection constantl. Theefoe, 1 and 2 ae not included in eq.(5). The distance the HVC moved, d is a known value. q ( 2, 2) epeiments, we detected onl standing objects. Theefoe, the calculated optical flow in the XY image flows fom the cente of the hoizon to outside. The calculated optical flow in the logpola image flows upwad. If an unepected movement vecto was obtained, it was consideed a mistake of the template matching and that movement vecto was not used to measue the distance. In this pape, templates wee made b featue points in the image, and then the camea was moved fowad. The template matching was eecuted on the image afte moving. The optical flow in the image of the object was Figue 12: Epeimental image (XY image) Figue 13: Epeimental image (logpola image) π/2 logpola image π q ( 1, 1) Figue11: Optical flow of logpola image Figue 14: Result of the detected the optical flow (XY image) D 1 e 1 = d (5) 2 1 e e 5 Epeiment We constucted epeiments to compae of the accuac of measuing the distance to an object using the XY image and logpola image obtained b the HVC. In these Figue 15: Result of the detected the optical flow (logpola image)
6 calculated b the diffeence in the position of the templates. In the situation of a single backgound, we put two objects with the flat suface at the same distance. The camea was moved fowad b a constant distance each time, and an image was taken at each distance. The distance between the camea and objects changed fom 55cm to 15cm b a 1cm step. Using the obtained images, we measued the distance in the XY image and the logpola image, and we obtained the accuac of the measuing the distance in each image tpe. Figue 12 shows an XY image, and figue 13 shows a logpola image used in the epeiment. Figue 14 and 15 show the esult of the detected optical flow in figue 12 and 13 espectivel. Figue 16 shows one of the esults of detecting the distance using an XY image, and figue 17 shows one of the esults of detected the distance using a logpola image. In the images of figues 1116, the actual distance to objects fom the camea is 3 cm. B the epeimental esult, the aveage eo in the XY image was 2.93 cm, while the aveage eo b the logpola image was 1.64 cm. The eason of this esult is that the template matching became easie b using the D Figue 16: Result of the detected the distance (XY image) D Figue 17: Result of the detected the distance (logpola image) logpola image, and the eo in the matching was educed. Theefoe, using the logpola image, we obtained the measued distance with highe accuac. 6 Conclusion In this pape, we pesented the effectiveness of the HVC, which is constucted b a mio and a camea fo a small obot sstem. Moeove, b using the popet of the HVC like the logpola image, the HVC can measue the distance to the object with highe accuac, and we conside that the HVC is ve useful fo the small obot sstem. In the futue, we have a plan to install the HVC in a cleaning obot. B using the lowe half of the image, the HVC can see the gound in font of it. B using the uppe half of the image, the HVC can know the obstacles aound it. Theefoe, the obot can easil find gabage and obstacles b using the obtained image. Refeence [1] K.Matsushita, K.Kato and K.Yamamoto: Development of the bid tacking sstem using intepolating backgound, Poc. of ISIRS 98, pp (1998) [2] T.Nakamua and M.Asada: Steeo Sketch: Steeo VisionBased Taget Reaching Behavio Acquisition with Occlusion Detection and Avoidance, Poc. of IEEE Int. Conf. on Robotics and Automation, pp (1996) [3] [4] T.Takeama, S.Yamamoto, K.Matsushita, K.Kato and K.Yamamoto: The Path Planning Method Using Topologicall Connected Neual Netwok fo Event Tacking Robot Sstem, Poc. of FCV 98, pp (1998) [5] A.Iwata, K.Kato and K.Yamamoto: "The Detective of the Obstacle b Using the New Sstem Called Hoizon View Camea", Poc. of ACCV22, Vol.1, pp (22) [6] S.Kaneko and T.Honda: Calculation of Positions of Polhedal Objects Using Diect and Mio Images, Jounal of JSPE, Vol.52, No.1, pp (1986) (in Japanese) [7] G.Adiv: Deteming 3D Motion and Stuctue fom Optical Flow Geneated b Seveal Moving Objects, IEEE, PAMI, Vol.7, No.4, pp (1985) [8] A K. Jain, Y Zhong and S.Lakshmanan: Object Matching Using Defomable Templates, IEEE, PAMI, Vol.18, No.3, pp (1996) [9] M.Tistaelli and G.Sandini, On the advantages of pola and logpola mapping fo diect estimation of timetoimpact fom optical flow, IEEE, PAMI, Vol.15, No.4, pp (1993) [1] T.Kuita, K.Hotta and T.Mishima: Scale and Rotation Invaiant Recognition Method using HigheOde Local Autocoelation Featues of LogPola Image, Poc. of ACCV1998, Vol.2, pp (1998)
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