Patent Application: US-93622809-A

Abstract:
using photographic flash for candid shots often results in an unevenly lit scene , in which objects in the back appear dark . a spatially adaptive photographic flash is disclosed , in which the intensity of illumination varies depending on the depth and reflectivity of features in the scene . adaption to changes in depth are used in a single - shot method . adaption to changes in reflectivity are used in a multishot method . the single - shot method requires only a depth image , whereas the multi - shot method requires at least one color image in addition to the depth data .

Description:
the setup consists of a spatially adaptive flash unit 100 as well as a color camera 40 . in a standard setup the spatially adaptive flash unit 100 is positioned , such that the location roughly corresponds to a conventional flash unit mounted on the hot shoe of the color camera 40 , cf . fig1 . this allocation of the different components has been chosen to get as close as possible to a candid shot setting . however , this setup with a wired communication 105 is not limited to this setting , since the spatially adaptive flash unit 100 could also be triggered — sometimes also called released — wirelessly from the camera 40 . however , if the spatially adaptive flash unit & lt ;& lt ; safu & gt ;& gt ; 100 is not attached rigidly to the camera 40 , the multi - shot approach — details see later on — would require recalibration each time either is moved . the spatially adaptive flash unit 100 consists of a projector 20 or a case 20 with lamp 21 , a lcd panel 23 and a lens 22 . the spatially adaptive flash unit 100 contains additionally a depth camera 30 based on time - of - flight ( tof ) technology . the conceptual or procedural setup is shown in fig2 . for a concrete embodiment of the invention , the light bulb from a projector sanyo plc - xw50 was removed and replaced by a canon speedlite 580ex ii . in order to increase the intensity from the spatially adaptive flash unit 100 , a mirrored tube 25 was built . this maximizes the light projected into the light path 24 . the rest of the light path 24 , including three lcd &# 39 ; s 23 , a lens 22 , and the depth camera 30 , are not modified . the alignment of the optical axis of the depth camera 30 and the optical axis of the lens 22 of the light are chosen to be as close as possible , in order to minimize the disparity between their views of the seen . the before mentioned tube was built in this embodiment , other embodiments are possible with such a tube 25 . a swissranger tof - camera 30 from mesa - imaging was employed . it has a resolution of 176 × 144 pixels , providing the depth and amplitude at a modulation frequency of 20 mhz . this allows for a depth range of 7 . 5 m without ambiguities . the tof - camera 30 has a built in illumination source , which operates in the infrared spectrum of 850 nm . the accuracy is highly dependent on the reflected amplitude as well as on the background illumination . according to [ büttgen et al .] the best depth accuracy lies in the mm range . the captured depth maps partially suffer from substantial noise , which has to be filtered . the color camera 40 is a canon eos 1d mark iii camera with a canon ef 16 - 35 mm f / 2 . 8 l usm lens . the camera 40 is either connected by usb bidirectionally to a personal computer ( not shown in the figures ) or bidirectionally to a processing unit 101 with a communication connection 102 . using a canon sdk all required settings of the camera 40 can be made . the distortion , as well as the extrinsic and intrinsic matrices of the depth camera 30 and the color camera 40 , are computed from six images of the printed checkerboard pattern . this method can be used for both types of cameras , since the checkers are also visible in the infrared spectrum of the depth camera 30 . the case 20 is calibrated relative to the color camera 40 based on the method presented in [ shen and meng 2002 ]. to increase the accuracy of the projector calibration , a novel checkerboard pattern of different color has been used . instead of taking a black checkerboard pattern , which has to be covered or removed in order to recognize the projected one , a blue colored and printed checkerboard pattern was used , while projecting white for the first image . the same printed checkerboard pattern is used as a projection surface for the second image . the projected pattern is a standard black and white checkerboard pattern . the calibration pattern can be extracted from the red channel for the first image , while it is extracted from the blue channel for the second image . this modification has the advantage , that the plane of reference will be exactly the same for both images , leading to a better accuracy , and more simplicity than the previous approach . it is important to note that this calibration has to be done only once , assuming the spatially adaptive flash unit 100 is mounted rigidly to the camera . fig2 shows the single - shot - method and multishot - method . both methods can be split into four steps : during the filter step , a median filter is applied to remove outliers in depths returned by the tof - camera 30 , and a novel trilateral filter is applied to reduce noise . the filtered depth data is then back projected , triangulated , and rendered into the case 20 view using graphics hardware . this step performs warping as resolves visibility in real - time . to cope with inaccuracies in calibration or depth values , a conservative depth discontinuity diffusion filter was applied . this filter gives depth values that are correct or slightly closer than the actual depth , thereby diminishing the visibility of possible misalignments . next an attenuation mask is computed . this computation takes as input the filtered depths , the virtual light position , and a user defined artistic filter . this attenuation mask is loaded onto the lcd - panel 23 of the spatially adaptive flash unit 100 , and a final image is captured by triggering the flash unit 100 and camera to fire via the release 41 . the single - shot method permits compensation for the unnatural falloff of a conventional flash by virtually repositioning the light source 21 further back — behind the photographer . to simulate the falloff of such a light source 21 , per - pixel depths are required . the time - of - flight camera 30 captures these depths at the same time the color camera is being aimed and focused . this method , where flash intensity is modulated based solely on depth , is called here as & lt ;& lt ; single - shot flash adjustment & gt ;& gt ;. the & lt ;& lt ; single - shot flash adjustment & gt ;& gt ; has the advantage of minimizing motion artifacts relative to methods that require multiple color images . however , variations in object reflectance cannot be taken into account by this method . assuming an already calibrated setup , the & lt ;& lt ; single - shot flash adjustment & gt ;& gt ; can be split into the following steps , see also fig2 : 1 acquisition of depth and amplitude ( infrared ); 2 depth filtering ; 3 reprojection from the depth - camera to the flash unit ; 4 per pixel , depth - dependent light adjustment ; 5 color camera capture . the acquisition using the depth - camera 30 is straight forward , and therefore for the person skilled in the art not elaborated any further . the captured depth data has a direct influence on the projected intensity per pixel . noise in the depth data is , therefore , also visible as noise in the evaluated illumination . since the human visual system is very sensitive to relative intensity variations , noise in the flash intensity becomes very easily visible . although increasing the exposure time of the depth camera 30 improves the signal noise ratio , it also increases motion blur artifacts . therefore , the noise is reduced by applying different filters on the depth data allowing to keep a short exposure time . bilateral filtering [ tomasi and manduchi 1998 ] has shown to perform well for filtering noise while preserving discontinuities in the signal . however , in order to remove the noise , the discontinuity of the signal always has to be higher than the noise level , which is not always the case when dealing with depth data from tof - cameras . eisemann and durand [ eisemann and durand 2004 ] and petschnigg et al . [ petschnigg et al . 2004 ] introduced the cross bilateral filter — also known as joint bilateral filter — as a variant of the classical bilateral filter . they use a low noise image , meaning a high confidence in the high frequency data , as input to the range weight . this avoids smoothing across discontinuities of the signal . this approach has been extended to a joint adaptive trilateral filter , where the noise model of the depth values of the tof - camera 30 is taken into account for the confidence of the range weights . according to [ büttgen et al . ], the standard deviation σ d of the depth data can be described as where c is the speed of light , f mod is the modulation frequency , bg is the background illumination , a sig is the mean number of electrons generated by the signal , and a is the measured amplitude in electrons . additional noise sources , such as thermal noise or dark current electrons are minimized by the camera and are neglected by this filter . since c and f mod are constant and c demod can be approximated by 0 . 5 according to [ büttgen et al . ], the standard deviation of the depth distribution is k = c 4 ⁢ π · f mod ⁢ 2 · 2 . this relationship shows that σ d , and therefore , the noise in the depth image , mainly depends on the amplitude . a joint adaptive trilateral filter has been introduced , which takes the amplitude dependent standard deviation σd of the depth values into account . the joint adaptive trilateral filter consists of a spatial proximity component g (•), a depth dependent component f (•) in the range domain and an amplitude dependent component h (•) in the range domain . the filtered depth value d m at position m can be described as : where a m and a i are amplitude values at position m and i respectively . the three functions g (•), f (•) and h (•) are chosen to be gaussian kernels , each with a kernel support of ω , and the corresponding standard deviations σ p , σ d and σ a respectively . intuitively , the filter is smoothing the depth values , while limiting the influence at depth or amplitude discontinuities . however , since the noise is not uniformly distributed , we adapt σd and σa , and therefore , the influence of f (•) and h (•). having a good approximation of the uncertainty measure of the depth values equation ( 1 ), the definition of two amplitude dependent functions σ d (•) and σ a (•) as follows : the initial standard deviation σ d int is set to a low value , while the is set to a high value , dropping to σ amin at a m = τ a . for very low amplitudes , the provided depth is very often an outlier . although the joint adaptive trilateral filter would be able to remove such outliers , it would require several iterations to do so . therefore , a median filter is applied , which removes the outliers in one step . to avoid unnecessarily blurring regions without outliers , the median filter has only two pixels with an amplitude below a threshold τ m . a threshold of τ m = 40 has shown to be a good value . to attenuate the light according to the depth values , they have to be transformed from the depth camera view to the projector view . in order to solve this reprojection step efficiently , a trivial triangular mesh is formed using all the back projected pixels from the depth camera and render them into the projector view . this provides a depth value per projector pixel and solves the visibility issue using the graphics card . artifacts can be introduced through resolution differences or remaining inaccuracies in the depth values . since there is not more information to improve the accuracy of the data during the single - shot acquisition , the quality of the result is improved by moving the error to regions where it is least visible . depth values that are too large produce visible artifacts , appearing as unexpectedly bright illumination . these artifacts are especially noticeable on objects close to the camera . similarly , depth values that are too small produce unexpectedly dim illumination . most of these artifacts appear at depth discontinuities . this means , that dim illumination due to too small depth values , will be adjacent to shadows produced by the flash and thus be less noticeable than the ones caused by too large depth values . therefore , it is advantageous to err on the side of computing depth values that are either correct or too shallow . this is referred as the & lt ;& lt ; conservative approach & gt ;& gt ;. one possibility to improve the depth data in a sense as to comply with the & lt ;& lt ; conservative approach & gt ;& gt ;, is shallow edge diffusion . first all the big depth discontinuities are extracted using a canny edge detector . then , the obtained edges are simplified to a contour and every vertex of it is moved in the direction of its local gradient towards the region with the bigger depth values . the amount of translation corresponds to the multiplication of a globally defined width and the local gradient of the vertex before translation . by connecting the first and last vertex of the original and the moved contour , a set p of points lying inside the polygon is created . finally , a modified bilateral filter is applied , cf equation ( 8 ) to all the depth values d m lying inside of p , such that the depth edge is filtered and moved towards the region of bigger depth . the value k c is normalizing the weights of the depth values d i . g (•) and h p (•) are two gaussian kernels defined on the support ω p . d imin corresponds to the shallowest depth value of the kernel support . the intensity i 0 of an illumination source at distance 1 decreases with the distance d to an intensity of this intensity falloff becomes visible in flash - photography and leads to unnaturally lit scenes . a light source positioned further behind the photographer , would result in a more homogeneously lit scene , which would appear more natural . based on the depth values obtained from the previous step , a spatially dependent attenuation function can be evaluated , the more desirable light position as a virtual light source can be simulated . the photographer can choose two interdependent parameters , namely the position of the virtual light source along the optical axis of the spatial adaptive flash unit 100 , and the minimal illumination for a specific subject of the scene . these preferences determine the depth compensation function leading to an attenuation per pixel . the attenuation can in fact be interpreted as a filter by which the flash light is being modulated . it can also be used as artistic filters giving the photographer more creative freedom . the parameters , which can be set by the user , are chosen based on the possible needs of the photographer . on the one hand , the photographer wants to pick the position of the light , and on the other hand , he wants to choose how much light is added to the subject of interest . the former can be set by providing the depth offset d off relative to the photographers position , with the positive axis lying in front of the photographer . the latter is defined by an intensity of the flash at the depth corresponding to the focal length d sub of the camera . it is believed , that this is a natural way of parameterizing the virtual light source , since the photographer wants to primarily have control over how much light is added to the subject in focus . especially for hand - held shots , the exposure time should not drop below a certain threshold to avoid motion blur due to camera shake . of course , this method is not limited to this parameterization , but it is the one to be most useful for candid shot settings . given the final depth values and the user parameters ( both see above ), a depth compensation function f c (•) can be defined as f c ⁡ ( d i ) = i sub · ( d sub - d off ) 2 · d i 2 ( d i - d off ) 2 · d sub 2 ( 9 ) f att ⁡ ( d i ) = { i max - f c ⁡ ( d i ) if ⁢ ⁢ f c ⁡ ( d i ) & lt ; i max 0 if ⁢ ⁢ f c ⁡ ( d i ) ≥ i max ( 10 ) with d i being the depth value at the pixel with index i . f c ( d i ) corresponds to the intensity that a pixel at index i requires to compensate for the position of the virtual light source . f att (•) is the attenuation function dimming the maximal lamp power of the spatially adaptive flash unit 100 to result in a projection intensity of f c (•). since the compensation function is limited , a maximal compensation depth d cmax can be defined as d cmax = - i max ⁢ d sub - i max ⁢ i sub ⁡ ( d sub - d off ) 2 ⁢ d off ⁢ d sub i sub ⁢ d sub 2 - 2 ⁢ i sub ⁢ d sub ⁢ d off + i sub ⁢ d off 2 - i max ⁢ d sub 2 , ( 11 ) where i max = f c ( d cmax ). if d cmax is smaller than any depth in the scene , the system could notify the photographer about a possible underexposure and either recommend a lower i sub or a smaller offset d off . in addition to compensating for depth , one can also adapt the color balance to keep the lighting mood of the scene . the & lt ;& lt ; single - shot flash adjustment & gt ;& gt ; is limited by a low resolution depth image , as well as a low resolution infrared amplitude image . therefore , scenes featuring very fine detail might show artifacts due to wrong depth values . furthermore , the lack of color information does not allow to correct for varying reflectance properties and overexposed regions automatically . to improve on these two limitations , a & lt ;& lt ; multi - shot flash adjustment & gt ;& gt ; is introduced . since a color image has to be captured before taking the final shot with the corrected flash light , this is considered as a multi - shot approach . assuming an already calibrated setup as for the & lt ;& lt ; single - shot flash adjustment & gt ;& gt ;, the & lt ;& lt ; multi - shot flash adjustment & gt ;& gt ; can be split into following steps , see also fig2 : 1 acquisition of depth and amplitude ( infrared ), and two color images ; 2 depth filtering using high resolution color ; 3 reprojection from the up sampled depth - data to the flash unit ; 4 per pixel , depth - dependent light adjustment / reflectance correction ; 5 color camera capture . since most of the steps are very similar to the & lt ;& lt ; single - shot flash adjustment & gt ;& gt ; approach , the focus will be on the enhanced filtering and on the flash - tone - mapping as described in the following paragraphs . for reasons mentioned before , a good depth filtering is very important . usage of the high - resolution color image allows to filter and up - sample the low resolution depth data , and therefore , get higher detail . kopf et . al [ kopf et al . 2007 ] presented the joint bilateral up - sampling for images , where the mapping of corresponding areas between a low resolution image and a high resolution image is given . in the setup presented the depth data from the depth camera is mapped to the color camera by using the reprojection step described above . to improve the correspondences between the depth and the color values , the depth data is filtered according to the definitions given above prior to the mapping . as a result the trivially up - sampled depth data d ˜ is obtained being of the same resolution as the color image i ˜ . to improve the performance of the filtering step , a technique motivated by the joint bilateral up sampling [ kopf et al . 2007 ] is applied . d ~ m = 1 k c ⁢ ∑ p ⇃ ↾ ∈ ω ~ ⇃ ↾ ⁢ d ~ p ⇃ ↾ · g ~ ⁡ (  m - p ⇃ ↾  ) · h c ~ ⁡ (  i ~ m - i ~ p ⇃ ↾  ) ( 12 ) k c = ∑ p ⇃ ↾ ∈ ω ~ ⇃ ↾ ⁢ g ~ ⁡ (  m - p ⇃ ↾  ) · h c ~ ⁡ (  i ~ m - i ~ p ⇃ ↾  ) ( 13 ) instead of evaluating the full filter kernel , every n th pixel at position p on the filter kernel ω is evaluated . n is the ratio between the width in pixels of the color camera , and the width in pixels of the depth camera , and for the height respectively . the closer the depth camera and the color camera are to a paraxial setting , the closer this approach is to the joint bilateral up - sampling . the function g ˜ (•) and h ˜ c (•) are gaussian kernels with a kernel support of ω ˜ . the color at position m is referred to as i ˜ m . in the previous sections a method to adjust the amount of light per pixel depending on the per pixel depth value has been presented . however , the reflectance of the scene has not been taken into account . regions of the scene , which were not lit before adding the flash light , might saturate when doing so . therefore , not taking into account the reflectance , would not allow to compensate for this . using a flash tone - mapping with a locally variable projection , which is motivated by the dodging - and - burning approach presented by reinhard et . al in [ reinhard et al . 2002 ] is proposed in this invention . the response curve of the camera without flash g ( z i ) and the maximum extent of the response curve with flash g f ( z i ), can be defined as safu : g f ( z i )= ln ( δ t · e i + δf i ) ( 15 ) the image pixel values z i are only dependent of the irradiance e i and the chosen exposure time δt for the camera response . g ( z i ) can be determined using a method presented by debevec et . al [ debevec and malik 1997 ]. since the duration of the flash unit is usually much shorter than the exposure time , its response function g f ( z i ) does not depend on the exposure time . a new response curve g n ( z i ) for the camera - flash system has to be found , which is similar to the response curve g ( z i ) of the camera , but extends the camera &# 39 ; s dynamic range independently of per - pixel depth . furthermore , the response curve shall avoid overexposure in the flash - lit image . g n ( z i ) is bound by the lower bound g l ( z i ) and the upper bound g ( z i ). the lower bound is determined as g l ( z i )= ln ( δ te i + δf i max ) ( 16 ) = ln ( δ te i + min ( δ f xy ( z i ))), where ( 17 ) δ f xy ( z i )= e g ( i ′ xy ) − e g ( i xy ) ,∀ xyεi xy . ( 18 ) the image pixels i xy of the no - flash image at position ( x , y ), and the image pixels of the flash image i ′ xy lie in the same range as z i . the solution for g n ( z i ) can now be approximated as a linear scaling of g ( z i ) by factor k , see equation ( 19 ). i xy is the pixel value at coordinate x , y . z i is the intensity , which lies in the same range as the intensity values i . therefore , z i is used to describe the transfer function . but the z i could anytime be exchanged by i xy . complies with the lower bound g l ( z i ). g n ( z i ) could be smoothed slightly in order to avoid discontinuities in the fixed range . given g n ( z i ) the corresponding luminance contributed by the flash can be calculated as follows the scaling factor s xy of the required light per pixel ( x , y ) of the spatially adaptive flash unit 100 can now be evaluated as δ f imax = g n ( z i )− g ( z i ). assuming only direct light contribution by the case 20 , the maximum intensity of the corresponding case pixel will be scaled by the scaling factor s xy as well . 102 bi - directional communication connection from the processing unit to depth - camera agrawal , a ., raskar , r ., nayar , s . k ., and li , y . 2005 . removing photography artifacts using gradient projection and flash - exposure sampling . in siggraph &# 39 ; 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