JP2012204878A - Video data stream evaluation method and system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To evaluate a video data stream including plural broadcast channels nearly in real time.SOLUTION: This evaluation method first selects two or more video frames for a specific channel. The method extracts and decodes the selected video frames from the video data stream, compares one of the decoded video frames with another one of the decoded video frames or a video frame stored in advance, and generates evaluation of the video data stream on the basis of the comparison.

Description

  The present invention relates to the transmission of video data streams, and more particularly to monitoring and evaluating video data streams that include multiple broadcast channels.

  The technology for transmitting both video and audio data is changing from the conventional technology. For example, in a television broadcasting facility, an Internet connection through an Ethernet connection is used rather than a traditional transmission format such as a serial digital interface (SDI) or an asynchronous serial interface (ASI) through a coaxial cable. It is now preferred to transmit broadcast data using protocol (IP) transmission. Video compression techniques are used in connection with broadcast transmission to reduce the bandwidth required to transmit video over terrestrial broadcast, cable television, and satellite broadcast.

  Compressed video carried by the Ethernet / IP protocol is commonly referred to as “IP video” and includes Ethernet / IP transport as well as transmission to private homes as well as in professional facilities. IP video can efficiently carry hundreds of channels of video and audio in multiple formats. Channels can mix standard definition (SD) and high resolution definition (HD) content and are transmitted in different formats in parallel for multiple SD channels and multiple HD channels. A typical IP video stream is carried over a 10 gigabit per second (Gbps) connection, for example, on a trunk that connects to a regional substation, and a 1 Gbps Ethernet from a regional substation to a private home, for example. Carried on a physical link.

JP 2001-251650 A

  A significant problem facing the video broadcast industry is the inability to efficiently and effectively monitor the transmission quality of hundreds of channels of video and audio typically broadcast by a single broadcast provider. Video broadcast providers often do not realize transmission problems that have a significant impact on customer viewing conditions until quite some time has passed. Customers often have black video (black video), freeze video (frozen video), or block noise, even if there are occasional “glitch” sometimes. Many customers cannot tolerate frequent or long-running problems with video transmission, such as the emergence of blocky video.

  Customers who are frustrated with video transmission issues such as black video, frozen video, blocky video, etc., simply switch to another video provider, Easily become a former customer. Also, even if the customer eventually switches to another provider, service calls (telephones) from the customer can be very costly in terms of customer support and technical support resources. This is particularly costly for the provider, as the customer's phone call will require a field technician to be dispatched to the customer's premises.

  Thus, the ability to perform baseband measurements on hundreds of multiplexed video and audio channels is a key issue in the developing IP video surveillance area. Current systems typically monitor the transport layer for error information without specifically checking for baseband. For example, in older products, the transport layer monitors closely but only a little if any of the decoded baseband video. Since transmission problems can occur across both the transport layer and stretched baseband video and occur frequently, such systems are particularly inadequate for IP video. More recent products may attempt to measure decoded baseband video, but these cannot be monitored if the expanded baseband data channel exceeds 2-3 channels, It is impossible such as several hundreds of multiple channels in parallel.

  In embodiments according to the disclosed technology, several decoded basebands can be measured in near real time for hundreds of channels of Internet Protocol (IP) video, particularly for full line rates of 1 Gbps Ethernet links. . In some embodiments, both high speed monitoring and detailed monitoring can be supported, up to hundreds of channels of IP video carried in a high speed IP video stream, thereby providing a timely and valuable quality of experience (QoE) quality of measurement experience. a broadcast video provider with the ability to alert on the video quality provided to the customer.

  A first aspect of the present application is a machine-controlled video data stream evaluation method in which a channel including a plurality of video frames receives a plurality of video data streams from a video data source. Selecting at least two video frames from the plurality of video frames corresponding to one particular channel of the plurality of channels; and selecting the video frame selected from the video data stream Extracting each of the extracted video frames; and decoding at least one of the decoded video frames of another decoded video frame or a previously stored video frame. Comparing with at least one; At least in part on the basis of the comparison result of the serial comparison step and comprising a step of generating an evaluation of the video data stream.

  According to a second aspect of the present application, in the method according to the first aspect, the video data stream is one of Internet protocol (IP) video, satellite broadcast video, cable video, and terrestrial propagation video. It is characterized by.

  The invention of the third aspect of the present application is characterized in that, in the selection step of the method of the first aspect, at least two independent video frames (I frames) corresponding to one of the plurality of channels are selected. .

  According to a fourth aspect of the present application, in the selecting step of the method according to the first aspect, at least one independent video frame (I video frame) and at least one bi-directional video frame (B video frame). Alternatively, a predictive video frame (P video frame) is selected, and each of the video frames corresponds to the specific channel in the plurality of channels.

  According to a fifth aspect of the present application, in the method according to the first aspect, the selection is performed on at least two video frames in a plurality of video frames corresponding to one channel other than the specific channel among the plurality of channels. It is characterized by further executing the steps of extraction, decoding, comparison and evaluation creation.

  According to a sixth aspect of the present application, in the method according to the fifth aspect, the one channel other than the specific channel is selected from the plurality of channels based at least in part on a priority list including a number of channels equal to or less than the number of the plurality of channels. It is characterized by further comprising a step of selecting.

  According to a seventh aspect of the present application, in the method according to the first aspect, the selection, extraction, and extraction of at least two video frames of a plurality of video frames corresponding to each of the plurality of channels other than the specific channel, Subsequent to executing the decoding, comparison, and evaluation creation steps, the selection, extraction, decoding, comparison, and evaluation creation steps are repeated for the specific channel among the plurality of channels.

  According to an eighth aspect of the present application, the step of extracting in the method of the first aspect generates a composite data stream including information corresponding to each selected video frame; and formatting the composite data stream; Adding video frame specifying information corresponding to each selected video frame to the composite data stream, wherein the video frame specifying information includes channel information, timing, and the like. Contains at least one of information and metadata.

  According to a ninth aspect of the present application, the decoding step in the method according to the first aspect includes a step of preparing a decoder that receives the extracted video frame, a step of the extracted video frame passing through the decoder, and an output from the decoder Capturing the data, wherein the method of the first aspect further comprises the step of sending an error message to the control block in response to the error being decoded.

  A tenth aspect of the present application further includes a step of resetting the decoder in the evaluation generation step following the first decoding step in the method of the first aspect.

  According to an eleventh aspect of the present application, in the method according to the first aspect, the comparison step may have substantially black video appearing in the decoded video frame, or substantially freeze video may appear. It is characterized by having a step of generating a warning (alert) according to the determination that there is no.

  A twelfth aspect of the present application is the method according to the eleventh aspect, wherein when a warning is generated, the selection, extraction, decoding, comparison, and evaluation of the specific number of additional video frames in the video data stream are performed. By generating a second evaluation of the video frame.

  According to a thirteenth aspect of the present application, in the method according to the first aspect, the comparison step includes a step of generating a warning in response to a determination that block noise may appear in the decoded video frame. It is characterized by that.

  According to a fourteenth aspect of the present application, in the method according to the thirteenth aspect, when a warning is generated, the selection, extraction, decoding, comparison, and evaluation of the specific number of additional video frames in the video data stream are performed. By generating a second evaluation of the video frame.

  A fifteenth aspect of the present application is characterized in that the method of the first aspect further comprises the step of accumulating selected video frames.

  The sixteenth aspect of the present application records instructions that can be executed by a machine to execute the video data stream evaluation method according to the first aspect when executed on the machine. One or more possible media.

A seventeenth aspect of the present application is a video data stream evaluation system,
A video data receiver that operates to receive an incoming video data stream;
A video data selection module operable to select at least two video frames corresponding to one particular channel in the input video data stream;
A video data extraction module operable to extract the selected video frame from the video data stream;
A video data decoder operable to decode the video frame selected and extracted from the video data stream;
A video data comparison module operable to compare each of the decoded video frames against at least one reference video frame;
A video data evaluation module operative to generate a report for the particular channel based at least in part on the output information received from the video data comparison module.

  According to an eighteenth aspect of the present application, in the video data stream evaluation system according to the seventeenth aspect, at least one of the reference video frames is a different one of the decoded video frames or a previously accumulated video frame. Or is characterized by containing decoded video frames or pre-stored video frames.

  According to a nineteenth aspect of the present application, a video data stream evaluation system according to the seventeenth aspect stores a selected video frame, and the stored video frame is subsequently compared in a video data comparison module. It is further characterized in that it further comprises a storage module that operates to supply for the purpose.

  According to a nineteenth aspect of the present application, in the video data stream evaluation system according to the seventeenth aspect, the video data evaluation module operates to send a report on the specific channel to a designated recipient.

FIG. 1 is a block diagram illustrating an example of an elementary stream having different types of video frames. FIG. 2 is a block diagram illustrating an example of changing a video from a first resolution to a second lower resolution to change the application. FIG. 3 is a block diagram illustrating an example of a video data stream evaluation system in accordance with an embodiment of the disclosed technology. FIG. 4 is a block diagram illustrating an example video underframe processing module in accordance with embodiments of the disclosed technology. FIG. 5 is a block diagram illustrating an example of a multi-channel video data stream evaluation system according to an embodiment of the disclosed technology. FIG. 6 is a block diagram illustrating an example video data stream evaluation system having a fast scan and detailed scan evaluation module according to an embodiment of the disclosed technology. FIG. 7 is a flowchart illustrating an example of a machine-controlled video data stream evaluation method according to an embodiment of the disclosed technology. FIG. 8 is a flowchart illustrating another example of a machine-controlled video data stream evaluation method according to an embodiment of the disclosed technology.

  FIG. 1 is a block diagram depicting an elementary video data stream (ES stream) 100. In this example, the ES stream 100 includes independent (independent) frames (I frames) 102a and 102d, predictive (predictive) frames (P frames) 102b, and bi-directional (bidirectional: bi). -directional) frame (B frame) 102c. The I frames 102a and 102d are basically images that can be drawn by themselves, like still images. Since the P frame 102b and the B frame 102c hold only a part of the corresponding image information, respectively, a smaller storage capacity is required than the I frames 102a and 102d.

  P frame 102b only stores changes between the current frame and the previous frame (ie, the first I frame 102a), which is why P frames are also commonly referred to as "delta frames". For example, if the only change in the image between the I frame 102a and the P frame 102b is the character moving in the foreground of the image, the background pixels of the image that do not change are not stored in the P frame 102b. B frame 102c further identifies the displayed content using the difference between both the previous frame (ie, P frame 102b) and the subsequent frame (ie, I frame 102d) and the current frame, Save storage capacity.

  A packetized elementary stream (PES) typically includes a plurality of PES packets, each consisting of video data within an ES, such as ES 100 of FIG. A PES packet is typically divided into fixed size transport stream (TS) packets. The transport stream typically includes a plurality of 188 byte TS packets that can be easily multiplexed at one time and transmitted as part of an IP video stream using typical broadcast transmission techniques.

  FIG. 2 is a block diagram depicting a data reduction process 200 for converting high definition (HD) video data 202 to standard definition (SD) video data 204. For example, the HD video data 202 has a resolution of 1080i, and may be diverted to the SD video data 204, that is, the resolution may be reduced to 640 × 480. Also, in some situations it may be necessary to reduce the SD video data 204 to portable video data 206 so that it can be displayed on, for example, a handheld computer or cell phone. A common problem in diversion is that the image quality of the video data may deteriorate at each data reduction stage. For example, if an image is reduced from one resolution to a second lower resolution, the image may be soft and blurry on a device that displays the image at that lower resolution.

  For the video data stream, errors unique to each layer may occur, so it is necessary to monitor the error for each layer. Also, problems in one layer (eg, one IP packet) often lead to errors in other layers (eg, corresponding TS packets). In fact, one error caused by a broken video frame propagates to many video frames. If the combiner captures (selects) a bad bond point, it may need to be turned off by one bit, for example, to break the data stream. Some current systems have built-in error correction, but they are very limited. For example, some current systems support limited evaluation of a given transport stream or packetized elementary stream (PES).

  To complicate matters, new standards such as H.264 tend to require more processing power, and even the evaluation of only one channel, as well as hundreds of channels, will soon run out of processor power. It is. In fact, even a high-performance personal computer can handle only a few H.264 video streams due to its complexity. A hardware decoder typically can only process at most four H.264 video streams, and in that case, it only switches and processes them over time. This is because a very large amount of processing resources are required to decode all the data even if hardware having a very high capacity is used.

  It is preferable to measure in real time critical aspects of the decoded baseband, such as detection of black frames, freeze frames and blockiness. The black frame generally means that the display image remains substantially or completely black and cannot move. A freeze frame generally refers to a situation in which a display image remains stationary in one frame and basically repeats that frame. Blockiness generally refers to the appearance of visual artifacts with block shapes or rectangular edges. A person skilled in the art will understand that a display image in which such behavior appears includes noise. For example, a black frame might mean that the viewer is stuck in a black display, but in reality there is some noise and the data is not actually perfectly uniform. .

  FIG. 3 is a block diagram of an example video data stream evaluation system 300. A video source 302 provides a video data stream to the video data stream evaluation system 300. A video data stream may include a number of separate broadcast channels. In this example, the video data stream evaluation system 300 includes a video frame under processing module 304 that receives a video data stream from a video source 302, for example with respect to the example shown in FIG. Can perform the pre-processing (pre-processing) such as the video frame format described in the above. In some embodiments, video frame down-processing module 304 may group video data for each video data format, such as HD data and SD data, as described in detail with respect to the example shown in FIG. .

  Once video data from one or more channels is properly formatted and optionally a set of video data combined with the same transformed data of other channels can be prepared, Module 304 can, for example, place video data at the head of a decoder queue, which results in video data being placed into decoder resources, eg, a video frame decode module. It can be sent to 306. The video frame decoding module 306 decodes the video frame received from the video frame lower processing module 304 and sends the decoded video frame to the video frame evaluation module 308.

  If the expected number of properly decoded video frames does not appear from the video frame decode module 306, an error may be sent to the control block, for example, to determine what action to take. . These situations can be caused by actual errors in the video data (which need to be evaluated in more detail by other processes), but such situations can also be It can also be caused by problems with the decoder such as not having enough time to preset the frame decode module 306 or not setting up data. In such a scenario, the video frame decode module 306 may retry, requesting more video data to be sent in the next cycle, or alerting a particular user. You may do it.

  Upon receiving the decoded video frame from video frame decode module 306, video frame evaluation module 308 selects a channel based on the decoded video frame received from video frame decode module 306. Perform the identified assessment. For example, the video frame evaluation module 308 can determine whether the video (video) exhibits any undesirable characteristics, such as the appearance of black, freeze or block noise.

  In some embodiments, the video frame evaluation module 308 may individually decode multiple decoded video frames, one at a time, using some of the many commonly used video frame comparison algorithms, for example. Multiple video frames are evaluated by comparison, by measurement by comparing to each other. Video frame evaluation module 308 may optionally store multiple video frame copies of at least one previous cycle for each channel for possible future evaluation, eg, for comparison. good.

  In some embodiments, for freeze frames, in order to effectively reduce the rate of error, for example, a separation time may be provided between multiple video frames from the same channel. If the video frames are approximately the same over a few second spread, it is much more likely that the video is really frozen than the adjacent frames are nearly similar, except for noise. This is because adjacent frames are usually highly correlated. Therefore, to effectively detect a black or frozen image, a video frame evaluation module 308 that compares at least two frames is required. Also, since device errors may be missed by simply looking at I-frames or IDR frames, video frame evaluation module 308 generally takes care of P-frames or B-frames in addition to I-frames. And observe.

  In some embodiments, the video frame evaluation module 308 can generate one or more reports 312 that are sent continuously, at a particular point in time, or in response to meeting certain conditions. For example, the video frame evaluation module 308 can be configured to send the report 312 only when the video exhibits certain characteristics. The report 312 may include warnings (alerts) or trigger warnings (not shown). For example, if a channel is currently frozen, the video frame assessment module 308 can issue a report 312 that includes an alert or alert 312 to the local technical support team. To start problem solving immediately. The report 312 may include various types of information such as which channel is malfunctioning, what symptoms are currently present on that channel, and how long the symptoms have been present.

  As part of the evaluation of the decoded video frame, the video frame evaluation module 308 can retrieve pre-stored video frames from a frame repository 310 such as an internal or remote database. For example, the video frame evaluation module 308 can compare any of a number of previous video frames, such as the most recent previous video frame, with a number of current video frames. Also, since the video frame evaluation module 308 can store the video frame just evaluated in the frame storage 310, the video frame evaluation module 308 can use them in the subsequent evaluation.

  In certain embodiments of the disclosed technology, cost-effective and near real-time measurements can be made on hundreds of videos in an IP video stream. For example, consider the case of an IP video stream having 500 channels. In an embodiment that includes two 60-frame-per-second hardware decoders, one cycle through all 500 channels can be completed in 12 seconds, assuming an average of 3 frame times per channel.

  One skilled in the art will appreciate that the video data stream evaluation system 300 can be implemented in many different ways. For example, the individual components of video data stream evaluation system 300 can be implemented with hardware elements, software elements, or a combination of these. In embodiments that include hardware elements, the components may be separate from one another, part of one hardware element, or a combination thereof.

  One skilled in the art will appreciate that the disclosed technology includes an audio data stream evaluation system in addition to (or instead of) a video data stream evaluation system. In some embodiments, a single data stream evaluation system, such as video data stream evaluation system 300 of FIG. 3, is configured to handle both audio and video data corresponding to each of a number of broadcast channels. it can.

  FIG. 4 is a block diagram illustrating a detailed example of the video frame lower processing module 304 of FIG. In this example, video underframe processing module 304 includes a video frame selection module 402, which for at least two video channels for one particular channel from a video data stream received from video source 302. Select a frame. Use the video frame selection module 402 to significantly reduce data by reading through the incoming video stream and selecting only the two video frames that are ultimately sent to the decode resource for each channel it can. Finding video objects in a video stream requires significantly less processing resources than if everything was decoded.

  Video frame selection module 402 may select two I frames per channel. Alternatively, the video frame selection module 402 may select one I frame and one P frame or B frame. In yet another embodiment, video frame selection module 402 may select virtually any combination of I, P, and B frames. In some embodiments, video frame selection module 402 may select more than one video frame within a video stream.

  When a video frame is selected, the video frame selection module 402 may send the ID of the selected video frame to the video frame extraction module 404, thereby selecting from the video data stream. Extracted video frames are extracted. One skilled in the art will appreciate that the video frame selection module 402 and the video frame extraction module 404 may be implemented together or even as a single component. When the video frame extraction module 404 extracts the selected video frame, the selected video frame is sent to the video frame format module 406.

  The video frame format module 406 can format the extracted video frame received from the video frame extraction module 404. For example, once the position of the selected frame is identified, the video frame format module 406 puts the data into a pending state and sets it to a format suitable for use by the video frame decode module 306. . In some embodiments, video frame format module 406 can generate one or more composite data streams, each of which is suitable for decoding corresponding video data by video frame decode module 306. Copy to. The video frame format module 406 can take into account various details of the MPEG format such as decoding time stamp (decoding time information), presentation time stamp (presentation time information) and metadata, which are video Modifications may be made as necessary to ensure proper operation of the frame decode module 306.

  FIG. 5 is a block diagram illustrating a variation of the video data stream evaluation system 300 of FIG. 3 to handle multiple channel formats. In this example, the video frame processing module 304 processes the same type of video frames together (batch processing) through the decoding process before sending data, thereby reducing the reset time and setup time of the decoder. Can be reduced. In some embodiments, the video frame sub-processing module 304 can generate a composite stream for each video format. As used herein, a composite stream generally refers to a newly constructed data stream, which is video data copied from the corresponding actual video stream (eg, some All video data in the format).

  By reformatting a relatively small set of extracted video frames into the format expected by the decoder that receives it, the system can avoid the need to reset the decoder and, as a result, generally do so. Loss of brazing time can be avoided. Since the number of different types of video frames is usually small (eg 5 formats), the use of several composite channels allows decoding even in situations involving hundreds of channels of video pipelining. -Very efficient processing can be performed with resources.

  In a situation where the video frame includes a mixture of SD video channels and HD video channels, for example, the video frame lower processing module 304 processes a plurality of SD channels at a time (batch processing) and performs the first synthesis. The first composite stream can be sent to the video frame decode module 306 as a stream. The video frame lower processing module 304 also processes a plurality of HD channels at a time (batch processing) into a second composite stream, and sends the second composite stream to another video frame decoding module 506. The video frame decode module 506 may decode the stream and pass the decoded frame to another video frame evaluation module 508, which may optionally generate a report 510 on the HD data. .

  In a situation where there are a plurality of HD channel variants, the video frame lower processing module 304 can batch process each variant. For example, the video frame lower processing module 304 of FIG. 5 batch-processes the modified version and sends it as a single stream to another video frame decoding module 512. Module 512 decodes the plurality of video frames and sends them to a third video frame evaluation module 514. Module 514 may optionally generate a report 516 regarding the variant.

  The video data stream evaluation system 300 of FIG. 5 is shown in three separate sets of video frame decoding modules 306, 506 and 512 and video frame evaluation modules 308, 508 and 514, respectively. However, those skilled in the art will appreciate that, as another embodiment, one video frame decoding module or one video frame that processes multiple groups of multiple streams instead of multiple separate decoding resources and evaluation components. It will be understood that an evaluation module may be included.

  FIG. 6 is a block diagram illustrating an example of the video data stream evaluation system 300 of FIG. These include a fast scan video evaluation module 602 and a deep scan video evaluation module 604. In this example, the fast scan video evaluation module 602 can perform a fast scan for certain errors such as black, freeze or block noise appearing. As used herein, fast scan refers to a continuous scan of a number of different channels, at which time the fast scan video evaluation module 602 determines that 1 before proceeding to the next channel to evaluate. Select, extract and evaluate the minimum number of frames per channel, eg, 2 frames.

  The fast scan video evaluation module 602 performs a fast scan across all channels. However, this has a limit in detail (deep), and there is a limit in the amount of data to be inspected per channel. In this way, a measurement is performed on a limited set of basebands for a channel, the results for that channel are reported, and the cycle to the next channel is fast, typically near real time. Go on. If the fast scan video evaluation module 602 detects what may be a trigger, for example, a potential black video or freeze video, the video data stream evaluation system 300 may use a detailed scan video evaluation module 604. And spend more time examining the channel to see if the suspicious condition really exists.

  As used herein, deep scan or deep dive generally refers to a longer and more detailed video analysis of a channel. Detailed scans efficiently consider suspicious things in high-speed scans and convert them into highly reliable results. For example, if a fast scan by the fast scan and video evaluation module 602 appears to show that a particular channel is frozen, then the detailed scan and video evaluation module 604 may cause the channel to really freeze. Observe that channel in detail over a few seconds and get reliable results. Another situation in which the detailed scan may be activated is when the configuration of a GOP (group of pictures) is changed for a certain channel. In such a situation, the detailed scan video evaluation module 604 may cause the baseband video to have problems due to changes in the GOP or to pay more attention to the channel than normal.

  In one embodiment, the detailed scan video evaluation module 604 may be driven by a list of channels to be evaluated. This list can indicate priorities for a plurality of channels. For example, this list can be prioritized for detailed analysis, for example, for channels identified by a fast scan process or user request from an external automated video management system. This list allows the detailed scan video evaluation module 604 to perform a detailed scan for a specific channel or more frequently for a higher priority channel, such as a pay-per-view channel, for example. Can be managed. For example, the detailed scan / video evaluation module 604 can be set to perform detailed scan continuously for all channels even when the detailed scan processing is not performed according to the list.

  In some embodiments, smart alarm processing and engine control may be used to set up a list of channels to observe. Smart alarm processing and engine control can also specify a number of video characteristics to be detected and tracked by the system. In some embodiments, smart alarm processing and engine control can receive analysis results, such as report 312 of FIG. 3, for example, to determine how to handle that information. Based on that information, smart alarm processing and engine control can generate an alarm and determine, for example, whether to send the alarm to a particular user or network management system.

  FIG. 7 is a flow chart illustrating an example of a video data stream evaluation method 700 under machine control. In step 702, two or more video frames are selected for a particular channel in the incoming video data stream. In some embodiments, the system may start from the beginning of an I frame or IDR frame. Once more than one frame has been selected for the channel, they can be extracted from the video data stream as shown in step 704. In one embodiment, extraction refers to copying video data corresponding to a selected video frame into a newly generated composite stream.

  In step 706, the extracted video frame is formatted before being sent to the decoding resource. The formatted video frame is then decoded as shown in step 708. In embodiments where the decoding resource has already decoded some video frames, the decoding process may begin by resetting the decoder and preparing to receive the next data set. When the decoder is ready, the video data can be transmitted through the decoder and its output captured. Then, tags such as channel information, timing information, and other metadata (decoder flag, etc.) are attached to the obtained frame before being sent to the evaluation resource.

  In step 710, the formatted video frame received from the decoder is evaluated. For example, multiple video frames can be used to determine whether certain undesirable characteristics, such as black video, freeze video, or block noise, are present in the video frame being evaluated. Evaluation may be made in comparison or in comparison with previously stored video frames. As shown in step 712, an evaluation result is generated and, optionally, the evaluation result is sent to one or more recipients in accordance with possible actions based on the result. For example, a broadcast video provider can recommend technical support personnel to take proactive attention about black or freeze videos detected on a channel before receiving a call from an angry customer.

  FIG. 8 is a flowchart illustrating a method 800 according to another example of machine-controlled video data stream evaluation. In step 802, two or more video frames are selected from the video data stream for a particular channel. In step 804, the selected video frame is extracted, formatted, and sent to the decode resource, which decodes the video frame as shown in step 806.

  In step 808, a determination is made as to whether any errors occurred during the decoding in step 806. If an error is detected, error processing may be activated as shown in step 810. For example, an error message may be sent to a designated recipient. If no error is detected, or if an error is detected but can be considered harmless, or unrelated to the current process, the video frame is evaluated as shown in step 812. For example, the system can determine whether the video currently being delivered to the channel is black, freeze or block noise. The evaluation at step 812 may include a fast scan of the channel.

  In step 814, a determination is made as to whether to perform a detailed scan for the channel to be evaluated. When a fast scan of that channel is detected that a black or frozen video may appear on that channel, the system will check to see if that particular characteristic is really appearing on that channel. , You can launch a detailed scan of that channel. If a detailed scan is to be performed, the process returns to step 802. If the possibility of black video or freeze video is confirmed, the system will observe a larger number of video frames for that channel for a longer period of time to obtain a reliable criterion. If a detailed scan is not performed, processing of the current channel can be stopped as shown in step 816. At this point, the method 800 can begin with the next evaluated channel.

  Although the embodiments shown for the disclosed technology are roughly focused on IP video, those skilled in the art will appreciate that they are also applicable to satellite, cable or terrestrial propagation media. The following is a general description of a machine suitable for implementing embodiments of the disclosed technology.

  The following description is intended to be a brief and general description of a suitable machine capable of implementing embodiments of the disclosed technology. As used herein, the term “machine” broadly encompasses a single machine or a system in which multiple machines or devices operating together are communicatively coupled. A typical machine may include computing devices such as personal computers, workstations, servers, portable computers, handheld devices, tablet devices, and the like.

  Typically, a machine has a system bus that includes a processor, memory (eg, random access memory (RAM), read-only memory (ROM), or other state-bearing media), storage device. A video interface and an input / output interface port are attached. The machine may also include an embedded controller such as a programmable or non-programmable logic device or array, an ASIC (Application Specific IC), an embedded computer, a smart card. Machines, at least in part, are not only directed by other machines, virtual reality environment interaction, biometric feedback, and other input signals, but also traditional input devices (eg, keyboards, mice, etc.) ) May be controlled by input.

  A machine may utilize one or more connections to one or more remote machines through communication means such as a network interface, modem, and the like. Multiple machines may be connected to each other by a physical or logical network such as an intranet, the Internet, a local area network (LAN), a wide area network (WAN), and the like. For those skilled in the art, network communications can be performed using a variety of wired or wireless short or long distance carriers and protocols including radio frequency (RF), satellite, microwave, IEEE 545.11, Bluetooth, optical, infrared, cable, laser. It will be appreciated that can be used.

  Embodiments of the disclosed technology include functions, processing procedures, data structures that, when accessed on a machine, result in the machine performing a task or defining a summary data format or low-level hardware context. This can be explained by referring to related data including application programs and instructions, or by considering them together. Relevant data can be recorded, for example, in volatile or non-volatile memory (eg, RAM and ROM) and other storage devices and associated storage media. This storage medium includes hard disk drives, flexible disk drives, optical storage media, flash memory, memory sticks, digital video disks, biological storage, and other tangible physical storage media Can be included.

  Relevant data can be distributed as packets, serial data, parallel data, propagated signals, etc. through a transmission environment including a physical or logical network, and can be used in a compressed or encrypted format. Relevant data is available in a distributed environment and the machine is stored locally for access or remotely.

  While the principles of the invention have been described and illustrated with reference to illustrated embodiments, the illustrated embodiments can be modified in arrangement and detail without departing from such principles and may be combined in any desired form. You will understand what you can do. And although the above description has focused on specific embodiments, other configurations are possible. In particular, expressions such as “according to an embodiment of the present invention” are used herein, but such phrases generally mean an embodiment that can be realized as a reference, and the present invention specifies It is not meant to be limited to the configuration of the embodiment. As used herein, these terms mean the same or different embodiments for reference and can be combined with other embodiments.

  As a result, the detailed description and accompanying materials in this application are merely illustrative and should not be construed as limiting the gist of the present invention, in view of the fact that the embodiments described herein can be widely modified. . The present invention includes all modifications included in the scope of the gist and the idea based on the following claims and equivalents thereof.

300 Video Data Stream Evaluation System 302 Video Source 304 Video Frame Under Processing Module 306 Video Frame Decode Module 308 Video Frame Evaluation Module 310 Frame Repository 312 Report 402 Video Frame Selection Module 404 Video Frame Extraction Module 406 Video Frame Format Module 506 Video Frame Decode Module 508 Video Frame Evaluation Module 510 Report 512 Video Frame Decode Module 514 Video Frame Evaluation Module 516 Report 602 Fast Scan Video Evaluation Module 604 Details Scan Video Evaluation Module 606 Report 608 Report

Claims (2)

A machine controlled video data stream evaluation method comprising:
Receiving a plurality of video data streams from a video data source, each of the channels including a plurality of video frames;
Selecting at least two video frames from the plurality of video frames corresponding to one particular channel of the plurality of channels;
Extracting the selected video frame from the video data stream;
Decoding each of the extracted video frames;
Comparing at least one of the decoded video frames with at least one of the other decoded video frames or previously stored video frames;
Generating a rating of the video data stream based at least in part on the comparison result in the comparing step. A video data receiver that operates to receive an incoming video data stream;
A video data selection module operable to select at least two video frames corresponding to one particular channel in the input video data stream;
A video data extraction module operable to extract the selected video frame from the video data stream;
A video data decoder operable to decode the video frame selected and extracted from the video data stream;
A video data comparison module operable to compare each of the decoded video frames against at least one reference video frame;
A video data stream evaluation system comprising: a video data evaluation module operable to generate a report for the specific channel based at least in part on output information received from the video data comparison module.

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