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 .
Response to Amendment
Applicants’ arguments filed on 14 April 2026 have been fully considered but they are moot in view of the new ground of rejection.
By the amendment filed 14 April 2026, claims 1, 15, and 21 have been amended, claim 22 has been added.
Claims 1-6, 8, and 10-22 are now pending.
Claims 1-6, 8, and 10-22 are rejected.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-6, 8, and 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over van Beek (US Pub. 2008/0107173) in view of Zavesky et al. (US 2021/0176290 A1).
Regarding claim 1, van Beek discloses a method of transmitting data by radio signals from at least one first entity, wherein van Beek discloses a wireless video transmission system transmitting multiple video streams from a server to multiple clients over a shared communication channel (van Beek ¶ [0017], Figs. 1 and 5B).
van Beek further discloses the first entity comprises a recognition module having circuitry programmed to recognize at least data fractions in the data to be transmitted, wherein van Beek discloses encoders/transcoders and centralized bitrate management for transmitted video streams (van Beek ¶ [0017], Figs. 1 and 5B).
van Beek further discloses circuitry that automatically requests from the data transmission rate manager a higher data transmission rate for the first entity in order to transmit data fractions of interest with a higher data transmission rate, wherein van Beek discloses a centralized multi-stream bitrate controller jointly computing optimal bitrates for multiple streams and providing bitrate targets to the encoders/transcoders (van Beek ¶ [0017], Figs. 1 and 5B).
van Beek does not specifically disclose:
recognizing the data fractions by analyzing content of the data to identify data fractions containing information of interest;
recognizing the data fractions prior to encoding;
identifying information of interest based on what the data depicts.
Liang discloses “content adaptive FRC” configured to “dynamically adjust an output frame rate ... as a result of analysis of the content of source video frames” (Liang ¶ [0018]).
Liang further discloses analyzing “the content of at least some of the video frames of the stream of source video frames” and dynamically adjusting output frame rates based on the analyzed content (Liang ¶¶ [0018]-[0021]).
Liang therefore discloses content-aware analysis performed on source video frames prior to downstream processing/output operations.
Zavesky discloses that a “content analysis model analyzes the incoming content to determine which segments contain complex video or audio content” and further discloses determining “rate of scene change, motion in the scene, recurrence of characters in a scene, technically deep diagrams, visual resolution,” “the model may also adapt or classify the speed of information provided by the content”, indicating “that the system should slow down, enhance, or repeat the presentation of this content”, and generating scores based on the analyzed scene content (Zavesky ¶ [0027]).
Zavesky therefore discloses recognizing data fractions containing information of interest based on what the data depicts, including scene-level visual and audio characteristics.
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify van Beek to incorporate Liang’s source-side content analysis and Zavesky’s semantic scene-content analysis in order to identify important or complex content prior to encoding and dynamically allocate higher transmission rates and encoding resources to content of greater informational significance, thereby improving transmission efficiency and quality for important content.
Regarding claim 2, van Beek discloses that the data transmission rate is adapted when the data to be transmitted is encoded and that the encoder adapts a quality parameter, resolution, and/or frame rate, thereby adapting the data transmission rate (paras. 21, 56).
Regarding claim 3, van Beek discloses that the encoder compresses the data to be transmitted and removes data with lower priority from the data to be transmitted and delays data for later transmission, thereby adapting the data transmission rate (para. 22).
Regarding claim 4, van Beek discloses that the data transmission rate manager automatically adapts the data transmission rate for the first entity (para. 22).
Regarding claim 5, van Beek discloses that the data transmission rate manager automatically adapts the data transmission rate for the first entity based on information obtained concerning a maximum available data transmission rate of a radio channel used by the first entity (para. 56).
Regarding claim 6, van Beek discloses that several first entities are provided which each provide data to be transmitted such that several data sources are provided, and wherein the data transmission rate manager provides information concerning the respective data transmission rates for the several first entities (para. 17).
Regarding claim 8, van Beek discloses that the recognition module includes circuitry that performs an initial analysis of the data to be transmitted with regard to the data transmission rate to be used for the data to be transmitted (para. 43).
Regarding claim 10, van Beek discloses that the request is automatically granted if possible due to boundary conditions and/or wherein the request has to be acknowledged by an operator manually (para. 56).
Regarding claim 11, van Beek discloses that a control module having control circuitry is provided via which the data to be transmitted is controllable (para. 17; Fig. 1).
Regarding claim 12, van Beek discloses that a quality of the data, a zooming, and/or a switching between data sources is controllable (para. 22).
Regarding claim 13, van Beek discloses that a second entity is provided that comprises the data transmission rate manager and/or receives the data to be transmitted, thereby establishing a data sink (para. 17; Fig. 1).
Regarding claim 14, van Beek discloses that an artificial intelligence module is provided which takes upcoming scenarios into account, thereby establishing a predictive adaptation of the data transmission rate (para. 56).
Regarding claim 15, van Beek discloses a system for transmitting data by radio signals, wherein the system comprises: a first entity configured to transmit data with a data transmission rate by the radio signals, thereby establishing at least one data source, wherein van Beek discloses a wireless video transmission system transmitting multiple video streams from a server to multiple clients over a shared communication channel (van Beek ¶ [0017], Figs. 1 and 5B).
van Beek further discloses wherein the first entity comprises an encoder that is configured to encode the data to be transmitted wherein van Beek discloses encoders/transcoders configured to encode and adapt transmitted video streams (van Beek ¶ [0017], Figs. 1 and 5B).
van Beek further discloses the data transmission rate manager having circuitry configured to provide information concerning the data transmission rate for the first entity, wherein the encoder is configured to adapt the data transmission rate dynamically based on the information of the data transmission rate manager, wherein van Beek discloses a centralized multi-stream bitrate controller jointly computing optimal bitrates for multiple streams and providing bitrate targets to the encoders/transcoders (van Beek ¶ [0017], Figs. 1 and 5B).
van Beek does not specifically disclose:
a recognition module programmed to recognize at least data fractions prior to encoding;
analyzing content of the data to identify data fractions containing information of interest;
identifying information of interest based on what the data depicts; and
circuitry that automatically requests from the data transmission rate manager a higher data transmission rate in order to transmit data fractions of interest with a higher data transmission rate.
Liang discloses “content adaptive FRC” configured to “dynamically adjust an output frame rate ... as a result of analysis of the content of source video frames” (Liang ¶ [0018]).
Liang further discloses analyzing “the content of at least some of the video frames of the stream of source video frames” and dynamically adjusting output frame rates based on the analyzed content (Liang ¶¶ [0018]-[0021]).
Liang therefore discloses content-aware analysis performed on source video frames prior to downstream processing/output operations.
Zavesky discloses that a “content analysis model analyzes the incoming content to determine which segments contain complex video or audio content” and further discloses determining “rate of scene change, motion in the scene, recurrence of characters in a scene, technically deep diagrams, visual resolution,” and generating scores based on the analyzed scene content (Zavesky ¶ [0027]).
Zavesky therefore discloses recognizing data fractions containing information of interest based on what the data depicts, including scene-level visual and audio characteristics.
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify van Beek to incorporate Liang’s source-side content analysis and Zavesky’s semantic scene-content analysis in order to identify important or complex content prior to encoding and dynamically allocate higher transmission rates and encoding resources to content of greater informational significance, thereby improving transmission efficiency and quality for important content.
Regarding claim 16, van Beek discloses that the dynamic adaption of the data transmission rate is based on statistical multiplexing and/or on minimum and maximum data transmission rates per data source (paras. 21–22, 43).
Regarding claim 17, van Beek discloses that the data transmission rate manager includes circuitry configured to obtain information concerning a maximum available data transmission rate of a radio channel used by the first entity (para. 56).
Regarding claim 18, van Beek discloses that the information is obtained by transmission parameters associated with a waveform of radio signals used for transmitting the data (para. 56).
Regarding claim 19, van Beek discloses that the system comprises at least one second entity that comprises the data transmission rate manager and/or is configured to receive the data transmitted by the first entity, thereby establishing a data sink (para. 17; Fig. 1).
Regarding claim 20, van Beek discloses that a control module having control circuitry is provided via which the data to be transmitted is controllable (para. 17; Fig. 1).
Claims 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over van Beek (US Pub. 2008/0107173) in view of Liang et al, Zavesky and Mockett (US Pub. 2009/0052450).
Regarding claim 21, van Beek discloses a method of transmitting data by radio signals from at least one first entity, wherein a dynamic forward error correction is implemented for the data transmission; providing data to be transmitted by the first entity which establishes at least one data source; providing information concerning a data transmission rate for the first entity by a data transmission rate manager; adapting the data transmission rate dynamically based on the information of the data transmission rate manager by an encoder of the first entity; and encoding the data to be transmitted by the encoder, wherein van Beek discloses dynamically adapting transmission characteristics and bitrate allocation for transmitted wireless video streams using encoders/transcoders and a centralized bitrate controller (van Beek ¶ [0017], Figs. 1 and 5B).
van Beek does not specifically disclose:
wherein the first entity comprises a recognition module having circuitry programmed to recognize at least data fractions in the data to be transmitted prior to encoding;
by analyzing content of the data to identify data fractions containing information of interest based on what the data depicts;
circuitry that automatically requests from the data transmission rate manager a higher data transmission rate for the first entity in order to transmit data fractions of interest with a higher data transmission rate; and
wherein the data transmission rate is dynamically adapted in response to changes in the forward error correction.
Liang discloses source-side analysis of source video frame content and dynamic adjustment based on analyzed content (Liang ¶¶ [0018]-[0021]).
Zavesky discloses semantic scene-level analysis including scene changes, motion in scenes, and identification of important content based on analyzed visual/audio characteristics (Zavesky ¶ [0027]).
Mockett discloses a dynamic forward error correction module configured to adjust error-correction rate upward or downward based on observed packet loss (Mockett ¶ [0058]).
Although Mockett does not explicitly disclose adjusting the data transmission rate, adjusting FEC redundancy necessarily affects the effective payload transmission rate because increasing FEC redundancy reduces available payload bitrate while decreasing redundancy increases available payload bitrate.
It would have been obvious to one of ordinary skill in the art at the time of the invention to incorporate Mockett’s dynamic FEC adjustment into the adaptive bitrate system of van Beek, as modified by Liang and Zavesky, in order to improve robustness, align redundancy levels with transmission conditions and content significance, and dynamically adapt effective transmission rates in response to changing forward error correction conditions while preferentially allocating higher transmission rates to semantically important content.
Regarding claim 22, Liang further discloses wherein the first entity comprises a capturing device that captures image data and/or video data, wherein Liang discloses a source video module providing source video frames for content analysis and adaptive frame-rate processing (Liang ¶¶ [0018]-[0021]).
Zavesky further discloses wherein the recognition module is configured to recognize data fractions containing information of interest by analyzing visual scene content depicted in the captured image data and/or video data, wherein Zavesky discloses analyzing scene content including “rate of scene change, motion in the scene, recurrence of characters in a scene, technically deep diagrams, visual resolution,” and generating scores based on analyzed scene content (Zavesky ¶ [0027]).
Zavesky further discloses to detect a change in the visual scene content compared to previously analyzed data fractions, wherein Zavesky discloses determining scene changes and motion in scenes for identifying complex or important content segments (Zavesky ¶ [0027]).
van Beek further discloses dynamically allocating bitrate targets and transmission resources for transmitted streams (van Beek ¶ [0017], Figs. 1 and 5B).
It would have been obvious to one of ordinary skill in the art at the time of the invention to incorporate Liang’s source-video capture analysis and Zavesky’s scene-change and motion analysis into the adaptive bitrate allocation system of van Beek in order to dynamically identify visually important scene changes and automatically allocate higher transmission rates to such content, thereby improving transmission quality and efficient allocation of wireless transmission resources for visually significant video data.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure (see form 892).
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/Luat Phung/
Primary Examiner, Art Unit 2468
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