DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-9 are rejected under 35 U.S.C. 102(a) as being anticipated by USPN 2021/0243352 top Mcelvain et al.
With regard to claim 1, Mcelvain discloses an information processing apparatus (fig. 4, camera 402) comprising:
an imaging unit which outputs data of a captured image captured using multiple pixels arranged on an image sensor (Fig. 4, image sensor 110 and Fig 2, sensor 110);
a memory which temporarily stores the data of the captured image output from the imaging unit (Fig. 2, raw image data is captured 280 and stored in memory data input handler 410 in Fig. 4); and
a first processor (Fig. 4, branch including combiner 416, preprocessor 420 and synthesizer 430) and a second processor (Fig. 4, Face detector 460) which execute processing using the data of the captured image stored in the memory (Fig. 4, input handler 410),
wherein the first processor controls the imaging unit to control the multiple pixels arranged on the image sensor to capture images under imaging conditions different for each of preset plural kinds of pixel groups in order to execute first processing using data of the captured images each of which is captured from each of the plural kinds of pixel groups (Fig. 4, the first processor is considered the branch including the combiner 416, preprocessor 420 and synthesizer 430. As shown in Fig. 1, The exposure time controller 100 takes the short and long exposure pixel values from the sensor and either generates an HDR image or adjusts the exposure times in order to recapture/adjust the captured image data. The plural kinds of pixels groups are the different long and short exposure captured pixels. See paragraph [0065]-[0067]), and
the second processor executes second processing using data of a captured image of one kind of pixel group among data of the captured images each of which is captured from each of the plural kinds of pixel groups captured by the imaging unit under the control of the first processor (Fig. 4, face detector 460 is considered to be the second processor. The face detector identifies faces in the image data and judges how to adjust exposure according to the measured goodness metric. See paragraphs [0068], [0080]-[0085], [0091] and [0112]).
With regard to claim 2, Mcelvain discloses the information processing apparatus according to claim 1, wherein the second processor executes, as the second processing, processing for detecting presence of a person from a captured image using the data of the captured image of one kind of pixel group among the data of the captured images each of which is captured from each of the plural kinds of pixel groups (Fig. 5, step 560, the face detector 460 performs face detection in the image. See paragraphs [0068], [0080]-[0085], [0091] and [0112]. The facial exposure operates iteratively and considers facial data from either or both the short and long exposure pixel sensors and adjusts the long and/or short exposure values accordingly. From paragraph [0085]: “…In this implementation, each iteration (except for the first one) is based upon raw image data generated with exposure times according as adjusted in the preceding iteration. Different iterations of one iterative optimization process may emphasize different goodness metrics and/or face exposure. For example, initial iterations may make adjustments of the long exposure time to reduce clipping at the low end of the HDR histogram and/or to improve face exposure, whereas later iterations adjust the short exposure time and make smaller adjustments to the long exposure time to optimize a goodness metric derived from the HDR histogram, such as an entropy based metric.”).
With regard to claim 3, Mcelvain discloses the information processing apparatus according to claim 2, wherein when repeatedly executing the second processing, the second processor switches the kind of pixel group of the data of the captured image used in the second processing among the data of the captured images each of which is captured from each of the plural kinds of pixel groups (See Fig. 5, The detected face image data is used to adjust the exposure time in both the long and short exposure time adjustment based on the goodness metric measured. The process is repeated iteratively by the feedback loop shown in in Fig. 5. See paragraphs [0068], [0080]-[0085], [0091] and [0112]. The facial exposure operates iteratively and considers facial data from either or both the short and long exposure pixel sensors and adjusts the long and/or short exposure values accordingly. From paragraph [0085]: “…In this implementation, each iteration (except for the first one) is based upon raw image data generated with exposure times according as adjusted in the preceding iteration. Different iterations of one iterative optimization process may emphasize different goodness metrics and/or face exposure. For example, initial iterations may make adjustments of the long exposure time to reduce clipping at the low end of the HDR histogram and/or to improve face exposure, whereas later iterations adjust the short exposure time and make smaller adjustments to the long exposure time to optimize a goodness metric derived from the HDR histogram, such as an entropy based metric.”).
With regard to claim 4, Mcelvain discloses the information processing apparatus according to claim 3, wherein when detecting the presence of a person in the second processing, the second processor uses data of a captured image of similar kind of pixel group as the data of the captured image from which the presence of the person is detected next time when executing the second processing (See Fig. 5, The detected face image data is used to adjust the exposure time in both the long and short exposure time adjustment based on the goodness metric measured. The process is repeated iteratively by the feedback loop shown in in Fig. 5. See paragraphs [0068], [0080]-[0085], [0091] and [0112]).
With regard to claim 5, Mcelvain discloses the information processing apparatus according to claim 4, wherein when not detecting the presence of a person in the second processing, the second processor switches to data of a captured image of a kind of pixel group different from the data of the captured image of the pixel group from which the presence of a person is not detected next time when executing the second processing (See Fig. 5, The detected face image data is used to adjust the exposure time in both the long and short exposure time adjustment based on the goodness metric measured. The process is repeated iteratively by the feedback loop shown in in Fig. 5. See paragraphs [0068], [0080]-[0085], [0091] and [0112]. The facial exposure operates iteratively and considers facial data from either or both the short and long exposure pixel sensors and adjusts the long and/or short exposure values accordingly. From paragraph [0085]: “…In this implementation, each iteration (except for the first one) is based upon raw image data generated with exposure times according as adjusted in the preceding iteration. Different iterations of one iterative optimization process may emphasize different goodness metrics and/or face exposure. For example, initial iterations may make adjustments of the long exposure time to reduce clipping at the low end of the HDR histogram and/or to improve face exposure, whereas later iterations adjust the short exposure time and make smaller adjustments to the long exposure time to optimize a goodness metric derived from the HDR histogram, such as an entropy based metric.”).
With regard to claim 6, Mcelvain discloses the information processing apparatus according to claim 1, wherein the first processor controls the imaging unit to control the multiple pixels to capture images at exposure times different for each of the plural kinds of pixel groups (See Figs. 2, 4 and 5, The exposure time controller evaluates the short and long exposure sensor pixel image data, and accordingly adjusts the exposure times to recapture the image based on the goodness metric measured. The process is repeated iteratively by the feedback loop shown in Fig. 5. Step 550. See paragraphs [0068], [0080]-[0085], [0091] and [0112]).
With regard to claim 7, Mcelvain discloses the information processing apparatus according to claim 6, wherein, as the first processing, the first processor synthesizes the data of the captured images captured at the exposure times different for each of the plural kinds of pixel groups to generate data of an image with extended dynamic range (Fig. 5 and paragraphs [0084]-[0085], The iterative process adjust exposure times of both the long and short exposure time sensors in order to generate or synthesize an HDR image. See also Fig. 4, synthesizer 430).
With regard to claim 8, Mcelvain discloses the information processing apparatus according to claim 1, wherein the multiple pixels are arranged in a matrix on the image sensor, and the plural kinds of pixel groups are pixel groups in units of one or more rows among the multiple pixels arranged on the image sensor (Fig. 12, The short and long exposure sensor pixels are grouped in rows as shown).
With regard to claim 9, the discussion of claim 1 applies.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WESLEY J TUCKER whose telephone number is (571)272-7427. The examiner can normally be reached 9AM-5PM Monday-Friday.
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/WESLEY J TUCKER/Primary Examiner, Art Unit 2661