PATENT DOCUMENT

Publication Number: US-9300969-B2
Application Number: US-55636309-A
Country: US
Kind Code: B2

Title: Video storage

Abstract:
Systems, methods, and devices for encoding video data are provided. For example, an electronic device for obtaining and encoding video may include image capture circuitry, motion-sensing circuitry, and data processing circuitry. The image capture circuitry may capture an uncompressed video frame, and the motion-sensing circuitry may detect physical motion of the electronic device. The data processing circuitry may encode the uncompressed video frame based at least in part on a quantization parameter, which the data processing circuitry may determine based at least in part on whether the motion-sensing circuitry has detected physical motion of the electronic device.

Claims:
What is claimed is: 
     
       1. An electronic device comprising:
 a camera to capture an uncompressed video frame; 
 motion-sensing circuitry to detect physical motion of the electronic device; and 
 data processing circuitry to encode the uncompressed video frame based at least in part on a quantization parameter, to compare a prediction error of a preceding encoded frame, representing a difference between the encoded frame and a source frame from which the encoded frame was coded, to the detected physical motion for the preceding encoded frame, and to select the quantization parameter based at least in part on the detected physical motion by the motion-sensing circuitry and the prediction error. 
 
     
     
       2. The electronic device of  claim 1 , wherein the motion-sensing circuitry comprises one or more accelerometers; magnetometer circuitry; or Global Positioning System circuitry; or any combination thereof. 
     
     
       3. The electronic device of  claim 1 , wherein the motion-sensing circuitry detects a quantity of physical motion of the electronic device. 
     
     
       4. The electronic device of  claim 1 , wherein the data processing circuitry selects the quantization parameter based at least in part on a quantity of physical motion of the electronic device detected by the motion-sensing circuitry. 
     
     
       5. The electronic device of  claim 1 , wherein the comparison of the predicted error to the detected physical motion is used to determine the degree to which the detected physical motion is used to select the quantization parameter. 
     
     
       6. The electronic device of  claim 5 , wherein the data processing circuitry decreases the degree to which the detected physical motion is used to select the quantization parameter when the predicted error does not correlate with the physical motion of the electronic device detected by the motion-sensing circuitry. 
     
     
       7. A method comprising:
 receiving, into data processing circuitry, a current uncompressed video frame from a camera and a previously-selected quantization parameter; 
 encoding, using the data processing circuitry, the current uncompressed video frame based at least in part on the previously-selected quantization parameter to obtain a current encoded video frame; and 
 selecting, using the data processing circuitry, a subsequent quantization parameter, based on a prediction error of a preceding frame, representing a difference between the encoded frame and a source frame from which the encoded frame was coded, for encoding a future uncompressed video frame from the camera based at least in part on a complexity of the current encoded video frame and a detected physical movement of the camera by motion-sensing circuitry for the current uncompressed video frame. 
 
     
     
       8. The method of  claim 7 , wherein the subsequent quantization parameter is selected based at least in part on the detected physical movement of the camera, wherein the detected physical movement of the camera includes a side-to-side motion with respect to the camera, a rotation with respect to the camera, or any combination thereof. 
     
     
       9. The method of  claim 7 , wherein the subsequent quantization parameter is selected based at least in part on a quantity of the deleted physical movement of the camera. 
     
     
       10. The method of  claim 7 , wherein the subsequent quantization parameter is selected to be lower than otherwise when a physical movement of the camera is detected. 
     
     
       11. The method of  claim 7 , wherein the subsequent quantization parameter is selected to be higher than otherwise when a physical movement of the camera is detected. 
     
     
       12. The method of  claim 7 , wherein the subsequent quantization parameter is selected based at least in part on a direction of the detected physical movement of the camera. 
     
     
       13. The method of  claim 7 , wherein the subsequent quantization parameter is selected to be lower when a direction of the detected physical movement of the camera is perpendicular to a facial direction of the camera than when the direction of the detected physical movement of the camera is parallel to the facial direction of the camera. 
     
     
       14. An electronic device comprising:
 a camera to capture an uncompressed video frame; 
 motion-sensing circuitry to detect physical motion of the camera; and 
 data processing circuitry to encode the uncompressed video frame in accordance with a quantization metric and to select the quantization metric, based on a prediction error of a preceding frame, representing a difference between the encoded frame and a source frame from which the encoded frame was coded, and a quantity of physical motion of the camera detected by the motion-sensing circuitry and based on a relationship between historical statistics regarding prior-encoded video frames indicating the quantity of physical motion of the camera detected by the motion-sensing circuitry when the prior-encoded video frames were captured and a quantity of motion in prior uncompressed video frames. 
 
     
     
       15. The electronic device of  claim 14 , wherein the data processing circuitry encodes the uncompressed video frame using an encoding technique in compliance with the MPEG-1 standard; the MPEG-2 standard; the MPEG-4 standard; the H.261 standard; the H.263 standard; or the H.264 standard; or any combination thereof. 
     
     
       16. The electronic device of  claim 14 , wherein the data processing circuitry selects the quantization metric by selecting from one of a plurality of quantization parameters. 
     
     
       17. The electronic device of  claim 14 , comprising a memory device to store the historical statistics regarding the prior-encoded video frames indicating the quantity of physical motion of the camera detected by the motion-sensing circuitry when the prior-encoded video frames were captured and the quantity of motion in the prior uncompressed video frames. 
     
     
       18. The electronic device of  claim 14 , wherein the data processing circuitry determines a relationship between historical statistics regarding the prior-encoded video frames indicating the quantity of physical motion of the camera detected by the motion-sensing circuitry when the prior-encoded video frames were captured and the quantity of motion in the prior uncompressed video frames. 
     
     
       19. The electronic device of  claim 14 , wherein the data processing circuitry selects the quantization metric by selecting a fewer number of quantization steps than otherwise when the motion-sensing circuitry indicates a quantity of motion of the camera and a relationship exists between the historical statistics regarding the prior-encoded video frames indicating the quantity of physical motion of the camera detected by the motion-sensing circuitry when the prior-encoded video frames were captured and the quantity of motion in the prior uncompressed video frames. 
     
     
       20. A method comprising:
 receiving an uncompressed video frame from a camera into data processing circuitry; 
 receiving a motion-sensing input from motion-sensing circuitry indicating physical movement or non-movement of the camera into the data processing circuitry; and 
 encoding the uncompressed video frame in the data processing circuitry using a quantization parameter, based on a prediction error of a preceding frame, representing a difference between the encoded frame and a source frame from which the encoded frame was coded, and the motion-sensing input indicating physical movement of a compressed frame preceding the uncompressed video frame and a complexity of the compressed video frame preceding the uncompressed video frame. 
 
     
     
       21. The method of  claim 20 , wherein the uncompressed video frame is encoded using finer-grained encoding when the motion-sensing input indicates physical movement of the camera than when the motion-sensing input indicates physical non-movement of the camera. 
     
     
       22. The method of  claim 20 , comprising determining whether the physical movement or non-movement of the camera correlates with or is likely to correlate with motion of the uncompressed video frame, wherein the uncompressed video frame is encoded based at least in part on the determination of whether the physical movement or non-movement of the camera correlates with or is likely to correlate with motion of the uncompressed video frame. 
     
     
       23. The method of  claim 22 , wherein the uncompressed video frame is encoded using finer-grained encoding than otherwise when the physical movement of non-movement of the camera is determined to correlate with or be likely to correlate with motion of the uncompressed video frame and when the motion-sensing input indicates physical movement of the camera. 
     
     
       24. The method of  claim 20 , wherein the uncompressed video frame is encoded based at least in part on a quantity of physical movement of the camera indicated by the motion-sensing input. 
     
     
       25. The method of  claim 24 , wherein the uncompressed video frame is encoded using finer-grained encoding when the quantity of physical movement of the camera is higher than when the quantity of physical movement of the camera is lower. 
     
     
       26. A system comprising:
 a camera to obtain an uncompressed frame of video data; 
 motion-sensing circuitry to detect physical movements of the camera; and 
 data processing circuitry to predict a complexity of the uncompressed frame of video data using a quantization parameter, based on a prediction error of a preceding frame, representing a difference between the encoded frame and a source frame from which the encoded frame was coded, and physical movements of the camera detected by the motion-sensing circuitry and a complexity of a prior-encoded frame of video data and to encode the uncompressed frame of video data based at least in part on the predicted complexity of the uncompressed frame of video data based at least in part on the physical movements of the camera. 
 
     
     
       27. The system of  claim 26 , wherein the data processing circuitry is configured to predict, all other things being equal, a higher complexity when the motion-sensing circuitry detects physical movements of the camera than when the motion-sensing circuitry does not detect physical movements of the camera. 
     
     
       28. The system of  claim 26 , wherein the data processing circuitry encodes the uncompressed frame of video data using fewer quantization steps when the predicted complexity is higher and using more quantization steps when the predicted complexity is lower. 
     
     
       29. The system of  claim 26 , wherein a first electronic device comprises the camera and the motion sensing circuitry and wherein a second electronic device comprises the data processing circuitry. 
     
     
       30. The electronic device of  claim 1 , wherein the camera and the motion-sensing circuitry are disposed within the same housing. 
     
     
       31. The electronic device of  claim 1 , wherein the data processing circuitry selects the quantization parameter based on the degree of motion of the electronic device detected by the motion-sensing circuitry, and the physical motion is detected while the uncompressed video frame is captured by the camera. 
     
     
       32. The method of  claim 7 , wherein the camera and the motion-sensing circuitry are disposed within the same housing. 
     
     
       33. The electronic device of  claim 14 , wherein the camera and the motion-sensing circuitry are disposed within the same housing. 
     
     
       34. The electronic device of  claim 14 , wherein the physical motion of the camera is detected while the uncompressed video frame is captured by the camera. 
     
     
       35. The method of  claim 20 , wherein the camera and the motion-sensing circuitry are disposed within the same housing. 
     
     
       36. The method of  claim 20 , wherein the motion-sensing input from the motion-sensing circuitry indicates a degree of physical movement of the camera, and the physical movement of the camera is detected while the uncompressed video frame is captured by the camera. 
     
     
       37. The system of  claim 26 , wherein the camera and the motion-sensing circuitry are disposed within the same housing.

Description:
BACKGROUND 
     The presently disclosed subject matter relates generally to video coding techniques and, more particularly, to video coding techniques involving the selection of a quantization parameter (QP) and/or a data rate based on motion-sensing circuitry. 
     This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art. 
     Many video coding techniques, such as those outlined by standards such as MPEG-1, 2, and 4 and H.261, H.263, and H.264, achieve compression of video signals by removing redundant information. This information may include, for example, redundant temporal and/or spatial information in a series of video images. In addition, such video coding techniques may remove information that may otherwise by imperceptible to a user watching the decoded video. For example, one video coding technique may involve encoding a first video frame as a “key frame,” which may preserve substantially all information about the original video frame, and which may take up a significant amount of storage space. A series of subsequent frames may be encoded as “non-key frames,” which may include substantially only differences between the subsequent non-key frames and the key frame, and which may take up significantly less storage space. 
     During the encoding process, to relate the subsequent non-key frames to the key frame and previous non-key frames in decoding order, the subsequent frames may be predicted by the encoder based on information in the video frames. However, the predicted frames are unlikely to perfectly predict the actual video frame to be encoded. A difference between the original, uncompressed video frame to be encoded and the predicted frame may be referred to as prediction error. This prediction error may carry additional spatial details about the predicted frame. By applying a spatial transform to the prediction error, a corresponding decoder may obtain coefficients carrying spatial detail not present in the predicted frame. 
     Based on a desired video compression bit rate and a desired quality for a given frame, the encoder may apply a quantization parameter (QP) during the encoding process to the prediction error. The QP may represent one of a finite number of step sizes for use in transforming the prediction error. With a larger value of QP, the transformation may result in a video signal having a smaller number of bits. However, the video signal may produce a distorted image if the source video frame is particularly complex. On the other hand, smaller values of QP may produce more precisely reconstructed images, but may require a greater number of bits. Selecting a proper QP for encoding a current video frame may involve examining a series of future or prior video frames to predict motion in the frame. However, a system that lacks the capability to look ahead due to hardware limitations or practical considerations may be unable to select the proper QP in such a manner. 
     SUMMARY 
     A summary of certain embodiments disclosed herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure. Indeed, this disclosure may encompass a variety of aspects that may not be set forth below. 
     Present embodiments relate generally to systems, methods, and devices for encoding video with varying quantization based on detected image capture circuitry motion from motion-sensing circuitry. For example, an electronic device for obtaining and encoding video may include image capture circuitry, motion-sensing circuitry, and data processing circuitry. The image capture circuitry may capture an uncompressed video frame, and the motion-sensing circuitry may detect physical motion of the electronic device. The data processing circuitry may encode the uncompressed video frame based at least in part on a quantization parameter, which the data processing circuitry may determine based at least in part on whether the motion-sensing circuitry has detected physical motion of the electronic device. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Various aspects of this disclosure may be better understood upon reading the following detailed description and upon reference to the drawings in which: 
         FIG. 1  is a block diagram of an electronic device capable of performing video coding, in accordance with an embodiment; 
         FIG. 2  is a schematic representation of the electronic device of  FIG. 1 , in accordance with an embodiment; 
         FIG. 3  is a flowchart of an embodiment of a method for video coding, in accordance with an embodiment; 
         FIG. 4  is an exemplary plot relating quantization parameter (QP) and motion-sensing input over a period of time, in accordance with an embodiment; 
         FIG. 5  is a schematic representation of a video recording operation, in accordance with an embodiment; 
         FIG. 6  is an exemplary plot relating prediction error and a motion-sensing input signal over a period of time when the video recording operation of  FIG. 5  is employed, in accordance with an embodiment; 
         FIG. 7  is a schematic diagram of another video recording operation, in accordance with an embodiment; and 
         FIG. 8  is an exemplary plot relating prediction error and a motion-sensing input signal over a period of time when the video recording operation of  FIG. 7  is employed, in accordance with an embodiment. 
     
    
    
     DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS 
     One or more specific embodiments will be described below. In an effort to provide a concise description of these embodiments, not all features of an actual implementation are described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers&#39; specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure. 
     Embodiments of the presently disclosed subject matter may relate generally to systems, methods, and devices for performing video coding techniques. In particular, the present embodiments may relate to techniques for selecting a quantization parameter (QP) for encoding frames of video data. Since the selected QP may affect the bit rate and quality of encoded video frames, the QP may be selected as relatively lower when the frame to be encoded is accompanied with motion, so as to properly capture sufficient frame details. Similarly, the QP may be selected as relatively higher when the frame to be encoded is not accompanied with motion, as a lower QP may be unnecessary to preserve frame details during periods of non-motion, given the same complexity of target object(s) in both cases. 
     Rather than looking ahead to large numbers of future or prior video frames to estimate frame motion, the presently disclosed embodiments may involve estimating frame motion based on image capture circuitry motion detected by motion-sensing circuitry. Additionally, the detected motion may or may not be taken into account depending on whether the motion of the image capture circuitry, as determined by the motion-sensing circuitry, tracks the motion of captured video images. For example, the image capture circuitry motion may be considered when a stationary subject is captured by moving image capture circuitry, but not when moving image capture circuitry tracks the motion of a moving subject. 
     A general description of suitable electronic devices for performing the presently disclosed techniques is provided below. In particular,  FIG. 1  is a block diagram depicting various components that may be present in an electronic device suitable for use with the present techniques. Similarly,  FIG. 2  represents one example of a suitable electronic device, which may be, as illustrated, a handheld electronic device having image capture circuitry, motion-sensing circuitry, and video processing capabilities. 
     Turning first to  FIG. 1 , electronic device  10  for performing the presently disclosed techniques may include, among other things, central processing unit (CPU)  12 , main memory  14 , nonvolatile storage  16 , display  18 , user interface  20 , location-sensing circuitry  22 , input/output (I/O) interface  24 , network interfaces  26 , image capture circuitry  28 , and accelerometers  30 . By way of example, electronic device  10  may represent a block diagram of the handheld device depicted in  FIG. 2  or similar devices. Additionally or alternatively, electronic device  10  may represent a system of electronic devices with certain characteristics. For example, a first electronic device may include at least image capture circuitry  28  and motion-sensing circuitry such as accelerometers and/or location-sensing circuitry  22 , and a second electronic device may include CPU  12  and other data processing circuitry. 
     In electronic device  10  of  FIG. 1 , CPU  12  may be operably coupled with main memory  14  and nonvolatile memory  16  to perform various algorithms for carrying out the presently disclosed techniques. Display  18  may be a touch-screen display, which may enable users to interact with user interface  20  of electronic device  10 . Location-sensing circuitry  22  may represent device capabilities for determining the relative or absolute location of electronic device  10 . By way of example, location-sensing circuitry  22  may represent Global Positioning System (GPS) circuitry, algorithms for estimating location based on proximate wireless networks, such as local Wi-Fi networks, and/or magnetometer circuitry for estimating a current facial direction of electronic device  10 . I/O interface  24  may enable electronic device  10  to interface with various other electronic devices, as may network interfaces  26 . Network interfaces  26  may include, for example, interfaces for a personal area network (PAN), such as a Bluetooth network, for a local area network (LAN), such as an 802.11x Wi-Fi network, and/or for a wide area network (WAN), such as a 3G cellular network. 
     To record video, electronic device  10  may first capture a series of video frames with image capture circuitry  28 , which may take the form of a camera. The video frames may be encoded in specialized hardware in electronic device  10  or by CPU  12 , using video coding algorithms and the techniques disclosed herein. Specifically, during the video encoding process, a quantization parameter (QP) may be selected based on image capture circuitry  28  motion. Image capture circuitry  28  motion may be determined not only by analyzing the motion of current video frames, but based on motion signals from accelerometers  30  and/or location-sensing circuitry  22 . 
       FIG. 2  depicts handheld device  32 , which represents one embodiment of electronic device  10 . Handheld device  32  may represent, for example, a portable phone, a media player, a personal data organizer, a handheld game platform, or any combination of such devices. By way of example, handheld device  32  may be a model of an iPod® or iPhone® available from Apple Inc. of Cupertino, Calif. 
     Handheld device  32  may include enclosure  34  to protect interior components from physical damage and to shield them from electromagnetic interference. Enclosure  34  may surround display  18 , on which user interface  20  may display icons such as indicator icons  36 , which may indicate a cellular signal strength, Bluetooth connection, and/or battery life. I/O interfaces  24  may open through enclosure  34  and may include, for example, a proprietary I/O port from Apple Inc. to connect to external devices. 
     User input structures  38 ,  40 ,  42 , and  44  may, in combination with display  18 , allow a user to control handheld device  32 . For example, input structure  38  may activate or deactivate handheld device  32 , input structure  40  may navigate user interface  20  to a home screen or a user-configurable application screen, input structures  42  may provide volume control, and input structure  44  may toggle between vibrate and ring modes. Microphones  46  and speaker  48  may enable playback of audio and/or may enable certain phone capabilities. Headphone input  50  may provide a connection to external speakers and/or headphones. 
     Flowchart  52  of  FIG. 3  describes an embodiment of a method for encoding a frame of video using electronic device  10 . The method of flowchart  52  may be implemented in hardware or software of electronic device  10 , and may specifically involve selecting a quantization parameter (QP) based at least in part on motion sensing information from accelerometers  30  or location-sensing circuitry  22 . Flowchart  52  may begin with step  54 , which follows after a prior frame has been encoded and after the current encoding parameters, including the quantization parameter QP, have been obtained based on the prior-encoded frame. In other words, each current frame may be encoded based on parameters determined during the encoding of the prior frame. In step  54 , the encoding process may begin by obtaining an uncompressed current frame of video to be encoded. 
     The uncompressed current frame of video may be received from memory  14  or nonvolatile memory  16 , and may derive from image capture circuitry  28  or another source. If the current frame of video derives from another source, motion sensing data may accompany the uncompressed current video frame for subsequent processing at a later time. If the current frame of video derives from image capture circuitry  28 , motion sensing data from accelerometers  30  or location-sensing circuitry  22  may accompany the current frame for subsequent processing at a later time, or may be obtained at the time of subsequent processing, as described below. 
     In step  56 , encoding parameters obtained from the encoding of the prior frame may be obtained. The parameters may include, for example, the quantization parameter (QP), as well as an indication of frame type, or, specifically, whether the new frame is to be encoded as a key frame or a non-key frame. The QP may be one of a finite number of step sizes for approximating a spatial transform. By way of example, the QP may be a value from 0 to 51. Each increase by 1 in QP may represent a 12% increase in quantization steps. Thus, when the QP increases by 6, the corresponding step size may double. Higher step sizes may result in more crude approximations of spatial information during encoding. As such, higher values of QP may best suit images with relatively lower complexity, which may include images having relatively little motion. 
     The frame type parameter may indicate whether or not the current frame should be encoded as a key frame or a non-key frame. A key frame may represent a frame of video that can be decoded without referring to any other frame and will function as a reference frame for subsequent non-key frames. Thus, less video frame information may be removed during the encoding process if the current video frame is to be encoded as a key frame. Similarly, if the current video frame is to be encoded as a non-key frame, more video frame information may be removed, since non-key frames may simply provide data indicating changes from their reference frame(s). 
     Based on the parameters obtained in step  56 , the current frame may be encoded in step  58 . The encoding process of step  58  may be carried out in software or hardware, and may rely on techniques described, for example, by the MPEG-1, 2, or 4 specifications and/or the H.261, H.263, or H.264 specifications. The encoded video signal for the current frame may take up a certain number of bits depending on the complexity of the frame and the quantization parameter (QP) provided in step  56 . A higher frame complexity or lower QP may produce a video signal taking up more space, while a lower frame complexity or higher QP may produce a video signal taking up less space. 
     Additionally, the encoding process may involve determining a prediction error differing between the predicted encoded current frame and the actual, original uncompressed current frame. This prediction error may carry additional spatial details about the predicted frame. At a later time, during the decoding process prior to viewing the encoded video, a spatial transform may be applied to the prediction error, thereby obtaining coefficients carrying spatial detail not present in the predicted frame. The quantization parameter (QP) may relate to the step sizes of such a spatial transform. 
     In step  60 , encoding statistics, including the prediction error and/or the number of bits used to encode the current frame, may be obtained. In step  62 , the complexity of the recently-encoded current frame may be calculated. The calculated complexity may represent spatial and/or temporal complexity of the recently-encoded frame. 
     Step  64  may involve determining the quantization parameter (QP) and frame type to be employed for encoding a subsequent video frame, based on the complexity of the current video frame determined in step  62 , current motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 , and/or available storage or transmission bandwidth. As noted above, electronic device  10  may lack the memory and processing capabilities that may otherwise be required for determining a quantization complexity model based on future frames. Additionally, it may be undesirable to buffer a number of recently-recorded uncompressed frames prior to encoding a new frame, as doing so may create a latency between recording and encoding that may be noticeable if the video is to be played back immediately. Thus, in step  64 , rather than look ahead to future frames to determine future complexity and/or motion, electronic device  10  may employ motion-sensing information to serve as a proxy for such complexity and/or motion. 
     As such, in step  64 , image capture circuitry  28  motion data may be obtained or inferred from accelerometers  30  or location-sensing circuitry  22 . When such motion-sensing input is obtained from accelerometers  30 , the data may indicate when electronic device  10  is moved in certain directions. Motion in different directions, as detected by accelerometers  30 , may be interpreted as introducing a varying amount of image capture circuitry  28  motion into future video frames. For example, accelerometer  30  data indicating that electronic device  10  has moved in a direction forward or backward with respect to the orientation of image capture circuitry  28  may be interpreted as producing little image capture circuitry  28  motion, while accelerometer  30  data indicating that electronic device  10  has moved in a direction perpendicular to the orientation of image capture circuitry  28  or around an axis of image capture circuitry  28  may be interpreted producing significant image capture circuitry  28  motion. 
     In a similar manner, data from location-sensing circuitry  22  may also indicate varying degrees of image capture circuitry  28  motion, and may be used alone or in combination with accelerometer  30  data. If location-sensing circuitry  22  includes magnetometer circuitry for determining the orientation of electronic device  10  with respect to Earth&#39;s magnetic field, readings from the magnetometer circuitry may indicate when electronic device  10  is being rotated. Since rotating electronic device  10  may cause significant motion relative to the orientation of image capture circuitry  28 , magnetometer circuitry data obtained during such events may be used to approximate image capture circuitry  28  motion. Similarly, video may be recorded while electronic device  10  is being moved, which may occur while a user is walking while recording video or recording video from a moving vehicle. Thus, data from location-sensing circuitry  22  that indicates an amount of physical location change of electronic device  10  may thus also approximate image capture circuitry  28  motion under certain circumstances. 
     Though an approximation of image capture circuitry  28  motion via input from accelerometers  30  and/or location-sensing circuitry  22  may generally relate to the motion of recorded video frames, such motion-sensing input may not relate in all instances. As such, the quantization parameter (QP) calculated in step  64  may be chosen to reflect the motion-sensing input only if the predicted error matches the approximated amount of image capture circuitry  28  motion provided by accelerometers  30  and/or location-sensing circuitry  22 .  FIGS. 5-8 , discussed below, may illustrate such relationships. 
     In step  66 , the newly determined parameters for quantization parameter (QP) and frame type may be stored in the main memory  14  or nonvolatile storage  16 , to be employed in encoding the next video frame. In step  68 , with the current frame having been encoded, the process of flowchart  52  may return to step  54  to encode the next video frame. 
       FIG. 4  depicts exemplary plot  70 , which relates the proper quantization parameter (QP) factor for a series of video frames of similar complexity and the corresponding image capture circuitry  28  motion as indicated by motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 . First ordinate  72  of plot  70  represents a QP factor, normalized to a particular integer QP, from lower to higher. Second ordinate  74  represents a relative quantity of image capture circuitry  28  motion, as indicated by motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 , from more image capture circuitry  28  motion to less image capture circuitry  28  motion. Abscissa  76  represents increasing time, and may be understood to represent a series of video frames obtained and processed by handheld device  32  in accordance with flowchart  52  of  FIG. 3 . 
     As generally indicated by plot  70 , when the method of flowchart  52  is carried out, curve  78 , which represents quantization parameter (QP) factor, may generally track curve  80 , which represents motion-sensing input that approximates image capture circuitry  28  motion. Thus, when additional image capture circuitry  28  motion is detected by accelerometers  30  and/or location sensing-circuitry  22 , QP may correspondingly decrease. This decrease in QP may cause such moving video frames, which may generally have a greater complexity, to be encoded with greater precision, which may properly capture such increased complexity. In certain situations, such as when an amount of image capture circuitry  28  motion changes dramatically, such movement may be largely ignored, as shown by time interval  82  of plot  70 . 
     While plot  70  represents a general relationship between quantization parameter (QP) and motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 , under certain circumstances, the motion-sensing input may not actually indicate motion in captured video frames. As such, it may be undesirable to relate QP to motion-sensing input under such circumstances. When the motion-sensing input does not indicate motion in corresponding video frames, changes in predicted error determined in the encoding step  58  over a series of encoded video frames may not track the motion-sensing input.  FIGS. 5-8  illustrate variations in image capture circuitry  28  motion while recording video, as indicated by motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 , the resulting recorded video frames, and corresponding prediction errors. 
     Turning first to  FIG. 5 , video recording operation  84  illustrates using image capture circuitry  28  of handheld device  32  to record video images of subject  86 . Recorded video images of subject  86  may appear on display  18  as a series of video frames  88 . As depicted in  FIG. 5 , in video recording operation  84 , subject  86  is stationary. Thus, when a user moves handheld device  32  to the right, image capture circuitry  28  moves accordingly, and recorded video frames  88  show the movement of subject  86  to the left. 
     As video frames  88  are being obtained in video recording operation  84 , accelerometers  30  may indicate that handheld device  32  has moved to the right. Additionally, if handheld device  32  has rotated with respect to Earth&#39;s magnetic field, and/or if handheld device  32  moves a detectable distance, the magnetometer circuitry or the GPS circuitry of location-sensing circuitry  22  may indicate as such. The degree of motion indicated by accelerometers  30  and/or location-sensing circuitry  22  may be considered when quantization parameter (QP) is determined in step  64  of flowchart  52  of  FIG. 3 . As should be appreciated, in video recording operation  84  of  FIG. 5 , the amount of image capture circuitry  28  motion indicated by accelerometers  30  and/or location-sensing circuitry  22  may correspond to the amount of motion in recorded video frames  88 . 
     Plot  90  of  FIG. 6  compares prediction error and motion-sensing input for recorded video frames  88  over time, when the motion of image capture circuitry  28  corresponds to motion of the recorded video frames  88 , as generally may be obtained during video recording operation  84 . First ordinate  92  of plot  90  represents prediction error, which represents a difference between a predicted frame and an original uncompressed frame, as may be determined during the frame encoding of step  58  of flowchart  52  of  FIG. 3 . Since prediction error relates a predicted frame and an original frame, if the original frame includes a greater amount of motion than otherwise predicted, prediction error may increase. Second ordinate  94  of plot  90  represents a quantity of approximated image capture circuitry  28  motion sensed based on motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 . Abscissa  96  represents time as video frames  88  are recorded. As shown in plot  90 , prediction error curve  98  gradually increases in a manner that corresponds to motion-sensing input curve  100 . Since prediction error curve  98  largely tracks motion-sensing input curve  100  for recent prior frames, motion-sensing input indicating current image capture circuitry  28  motion may accordingly signify that motion is likely to occur in future frames as well. 
     Historical information, such as the information illustrated plot  90  relating prediction error and approximated image capture circuitry  28  motion, may be stored in memory during the frame encoding process of flowchart  52  of  FIG. 3 . Referring to step  64  of flowchart  52  of  FIG. 3 , when the quantization parameter (QP) for the subsequent frame is determined, such historical information may be considered. If the predicted error for a certain number of recent prior frames tracks the amount of image capture circuitry  28  motion indicated by motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 , the current amount of image capture circuitry  28  motion indicated by the motion-sensing input may be considered in determining QP. 
     In some embodiments, the degree to which the predicted error for a certain number of recent prior frames tracks the amount of image capture circuitry  28  motion, as indicated by motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 , may be considered during step  64  of flowchart  52  of  FIG. 3 . For example, a rate of increase in predicted error for a certain number of recent prior encoded frames may be related to a rate of increase in image capture circuitry  28  motion. This relationship may be used to estimate a degree of future video frame motion based on the degree of current image capture circuitry  28  motion, which may also be used for determining the appropriate quantization parameter (QP) for the frame. 
     Under certain other video recording circumstances, the prediction error may not match the motion-sensing input because image capture circuitry  28  motion may not be accompanied by video frame motion.  FIGS. 7 and 8  generally describe one such situation. Turning first to  FIG. 7 , video recording operation  102  illustrates using image capture circuitry  28  of handheld device  32  to record video images of subject  86 . Recorded video images of subject  86  may appear on display  18  as video frames  88 . As depicted in  FIG. 7 , in video recording operation  102 , subject  86  is moving to the right. Thus, when a user moves handheld device  32  to the right, image capture circuitry  28  moves accordingly, and subject  86  may remain largely stationary during recorded video frames  88 . 
     Plot  104  of  FIG. 8  compares prediction error and motion-sensing input for recorded video frames  88  over time, when the motion of image capture circuitry  28  does not correspond to motion in the recorded video frames  88 . Accordingly, plot  104  of  FIG. 8  may generally represent data obtained during video recording operation  102 . First ordinate  106  of plot  104  represents prediction error, which represents a difference between a predicted frame and an original uncompressed frame, as may be determined during the frame encoding of step  58  of flowchart  52  of  FIG. 3 . Since prediction error relates a predicted frame and an original frame, if the original frame includes a greater amount of motion than otherwise predicted, prediction error may increase with increased image capture circuitry  28  motion, and vice versa. Second ordinate  108  of plot  104  represents a quantity of approximated image capture circuitry  28  motion sensed based on motion-sensing input from accelerometers  30  and/or location-sensing circuitry  22 . Abscissa  110  represents time as video frames  88  are recorded. As shown in plot  102 , prediction error curve  112  gradually decreases, while motion-sensing input curve  114  increases, indicating that the two data are currently unrelated. Since prediction error curve  110  does not track motion-sensing input curve  114  for recent prior frames, motion-sensing input indicating an amount of current image capture circuitry  28  motion may be largely irrelevant regarding motion of video frames in the near future. 
     When the historical information comparing prediction error and approximated image capture circuitry  28  motion, which may be stored in memory during the frame encoding process of flowchart  52  of  FIG. 3 , does not indicate a relationship, motion sensing input from accelerometers  30  and/or location-sensing circuitry  22  may not be accorded much weight. In particular, during step  64  of flowchart  52  of  FIG. 3 , when the quantization parameter (QP) for the subsequent frame may be determined, motion-sensing input may be disregarded or considered only to the degree that recent historical data indicate a relationship between prediction error and image capture circuitry  28 . 
     The specific embodiments described above have been shown by way of example, and it should be understood that these embodiments may be susceptible to various modifications and alternative forms. It should be further understood that the claims are not intended to be limited to the particular forms disclosed, but rather to cover all modifications, equivalents, and alternatives falling within the spirit and scope of this disclosure.

Metadata:
Filing Date: 20090909
Publication Date: 20160329
Grant Date: 20160329
Priority Date: 20090909
Inventors: LINDAHL ARAM
LI WEI
Assignee: APPLE INC
CPC Classifications: [{"code": "H04N19/61", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/149", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/137", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04N19/124", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/124", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/61", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/149", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/124", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/61", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/149", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N19/137", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04N19/137", "inventive": true, "first": true, "tree": "[]"}]
Family ID: 43647462