Abstract: The present disclosure provides a computer-implemented method and system for performing real time supervised detection of televised video ads in a media content of a broadcasted channel. The method includes reception of the media content and selection of a set of frames per second from the media content. The method includes extraction of keypoints from each selected frame and derivation of binary descriptors from extracted keypoints. The method includes assignment of weight value to each binary descriptor and creation of a special pyramid of the binary descriptors. The method includes obtaining a first vocabulary of binary descriptors for each selected frame and accessing a second vocabulary of binary descriptors. The method includes comparison of each binary descriptor in the first vocabulary with binary descriptors in second vocabulary and progressively scoring each selected frame of the media content. The method includes detection of a first ad in the media content.

Abstract: The present disclosure provides a computer-implemented method and system for adaptively switching supervised detection strategy for watermarked and non-watermarked real time televised video advertisements. The televised video advertisements are present in a live stream of a media content of a broadcasted channel. The method includes selection of a set of frames per second from the media content. The method includes checking for one or more watermarked features in each selected frame of the media content. The method includes switching to a first detection strategy. The first detection strategy is associated with detection of a first ad in the live stream of the media content when the one or more watermarked feature are present in each checked frame in the selected set of frames.

Abstract: The present disclosure provides a computer-implemented method and system for adaptively reducing detection time in real time supervised detection of televised ads in media content of a channel. The method includes reception of the media content and selection of a set of frames per second from the media content. The method includes extraction of keypoints from each selected frame and derivation of binary descriptors from extracted keypoints. The method includes assignment of weight value to each binary descriptor and creation of a special pyramid of the binary descriptors. The method includes obtaining a first vocabulary of binary descriptors for each selected frame and accessing a second vocabulary of binary descriptors. The method includes comparison of each binary descriptor in the first vocabulary with binary descriptors in second vocabulary. The method includes progressively scoring each selected frame of the media content and detecting a first ad in the media content.

Abstract: The present disclosure provides a computer-implemented method and system for hardware, channel, language and ad length agnostic detection of multi-lingual televised advertisements. The detection is performed across live streams of media content of one or more broadcasted channels. The method includes selection of a set of frames per second from a pre-defined set of frames. The method includes extraction of a pre-defined number of keypoints from each selected frame and derivation of a pre-defined number of binary descriptors from the extracted keypoints. The method includes creation of a special pyramid of the binary descriptors and accessing a second vocabulary of binary descriptors. The method includes comparison of each spatially identifiable binary descriptor from the first vocabulary with spatially identifiable binary descriptors in clusters of the second vocabulary. The method includes progressively scoring each selected frame and detection of the first ad in the live streams of the media content.

Abstract: The present disclosure provides a computer-implemented method and system for progressive penalty and reward based ad scoring for real time supervised detection of televised video ads in televised media content. The method includes reception of the media content and selection of a set of frames per second from the media content. The method includes extraction of key points from each selected frame and derivation of binary descriptors from extracted key points. The method includes assignment of weight value to each binary descriptor and creation of a special pyramid of the binary descriptors. The method includes obtaining a first vocabulary of binary descriptors for each selected frame and accessing a second vocabulary of binary descriptors. The method includes comparison of each binary descriptor in the first vocabulary with binary descriptors in second vocabulary. The method includes progressively scoring each selected frame of the media content for detection of a first ad.

Abstract: The present disclosure provides a computer-implemented method and system for hardware, channel, language and ad length agnostic detection of multi-lingual televised advertisements. The detection is performed across live streams of media content of one or more broadcasted channels. The method includes selection of a set of frames per second from a pre-defined set of frames. The method includes extraction of a pre-defined number of keypoints from each selected frame and derivation of a pre-defined number of binary descriptors from the extracted keypoints. The method includes creation of a special pyramid of the binary descriptors and accessing a second vocabulary of binary descriptors. The method includes comparison of each spatially identifiable binary descriptor from the first vocabulary with spatially identifiable binary descriptors in clusters of the second vocabulary. The method includes progressively scoring each selected frame and detection of the first ad in the live streams of the media content.

Abstract: The present disclosure provides a computer-implemented method and system for adaptively switching supervised detection strategy for watermarked and non-watermarked real time televised video advertisements. The televised video advertisements are present in a live stream of a media content of a broadcasted channel. The method includes selection of a set of frames per second from the media content. The method includes checking for one or more watermarked features in each selected frame of the media content. The method includes switching to a first detection strategy. The first detection strategy is associated with detection of a first ad in the live stream of the media content when the one or more watermarked feature are present in each checked frame in the selected set of frames.

Abstract: The present disclosure provides a computer-implemented method and system for adaptively reducing detection time in real time supervised detection of televised ads in media content of a channel. The method includes reception of the media content and selection of a set of frames per second from the media content. The method includes extraction of keypoints from each selected frame and derivation of binary descriptors from extracted keypoints. The method includes assignment of weight value to each binary descriptor and creation of a special pyramid of the binary descriptors. The method includes obtaining a first vocabulary of binary descriptors for each selected frame and accessing a second vocabulary of binary descriptors. The method includes comparison of each binary descriptor in the first vocabulary with binary descriptors in second vocabulary. The method includes progressively scoring each selected frame of the media content and detecting a first ad in the media content.

Abstract: The present disclosure provides a computer-implemented method and system for performing real time supervised detection of televised video ads in a media content of a broadcasted channel. The method includes reception of the media content and selection of a set of frames per second from the media content. The method includes extraction of keypoints from each selected frame and derivation of binary descriptors from extracted keypoints. The method includes assignment of weight value to each binary descriptor and creation of a special pyramid of the binary descriptors. The method includes obtaining a first vocabulary of binary descriptors for each selected frame and accessing a second vocabulary of binary descriptors. The method includes comparison of each binary descriptor in the first vocabulary with binary descriptors in second vocabulary and progressively scoring each selected frame of the media content. The method includes detection of a first ad in the media content.

Abstract: A system and method for automated tagging of one or more advertisements broadcasted on a channel in real time includes a step of detecting the one or more advertisements broadcasted on the channel, and another step of fetching a set of prominent frames and a pre-defined section of an audio clip. The set of prominent frames and the pre-defined section of the audio clip correspond to a detected advertisement. The method also includes another step of retrieving plural features. The plural features corresponds to the set of prominent frames and the pre-defined section of the audio clip. The method also includes another step of comparing each of the plurality of features with corresponding pre-defined set of features. The method also includes another step of tagging the detected advertisement with a unique tag.

Abstract: A system and method for hardware agnostic detection of one or more advertisements broadcasted across one or more channels includes extracting a first set of audio fingerprints and a first set of video fingerprints. The method also includes generating a set of digital signature values corresponding to an extracted set of video fingerprints, and normalizing each frame of a pre-determined number of frames of a video. The method also includes scaling each frame of the corresponding pre-determined number of frames of the video clip to a pre-defined scale. Each frame corresponds to the broadcasted media content on the channel. The method also includes trimming a first pre-defined region and a second pre-defined region of each frame by a pre-defined percentage of a frame width, a frame height and a pre-defined number of pixels in each frame.

Abstract: A system and method for detecting one or more advertisements broadcasted on a channel in real time includes a step of receiving a live feed, with the live feed being associated with a media content broadcast on the channel in real time. The method also includes a step of deriving one or more characteristics associated with one or more properties associated with the channel. The method also includes a step of analyzing the one or more characteristics associated with the one or more properties. There is also a step of matching the derived one or more characteristics associated with the one or more properties with the stored one or more characteristics associated with the one or more properties. The method also includes a step of detecting the one or more advertisements broadcasted on the channel in real time.

Abstract: A system and method for detecting one or more advertisements broadcasted on a channel in real time includes a step of receiving a live feed, with the live feed being associated with a media content broadcast on the channel in real time. The method also includes a step of deriving one or more characteristics associated with one or more properties associated with the channel. The method also includes a step of analyzing the one or more characteristics associated with the one or more properties. There is also a step of matching the derived one or more characteristics associated with the one or more properties with the stored one or more characteristics associated with the one or more properties. The method also includes a step of detecting the one or more advertisements broadcasted on the channel in real time.

Abstract: A system and method for automated tagging of one or more advertisements broadcasted on a channel in real time includes a step of detecting the one or more advertisements broadcasted on the channel, and another step of fetching a set of prominent frames and a pre-defined section of an audio clip. The set of prominent frames and the pre-defined section of the audio clip correspond to a detected advertisement. The method also includes another step of retrieving plural features. The plural features corresponds to the set of prominent frames and the pre-defined section of the audio clip. The method also includes another step of comparing each of the plurality of features with corresponding pre-defined set of features. The method also includes another step of tagging the detected advertisement with a unique tag.

Abstract: A system and method for hardware agnostic detection of one or more advertisements broadcasted across one or more channels includes extracting a first set of audio fingerprints and a first set of video fingerprints. The method also includes generating a set of digital signature values corresponding to an extracted set of video fingerprints, and normalizing each frame of a pre-determined number of frames of a video. The method also includes scaling each frame of the corresponding pre-determined number of frames of the video clip to a pre-defined scale. Each frame corresponds to the broadcasted media content on the channel. The method also includes trimming a first pre-defined region and a second pre-defined region of each frame by a pre-defined percentage of a frame width, a frame height and a pre-defined number of pixels in each frame.

Abstract: A system and method for detecting one or more advertisements broadcast on a channel in real time includes a step of extracting a first set of audio fingerprints and a first set of video fingerprints. The first set of audio fingerprints and the first set of video fingerprints correspond to a media content broadcast on the channel. The method also includes a step of generating a set of digital signature values. The set of digital signature values corresponds to an extracted set of video fingerprints. The method also includes a step of detecting the one or more advertisements broadcast on the channel with the processor. The first set of video fingerprints and the audio fingerprints is extracted sequentially in the real time.

Abstract: A system and method for standardizing media content for channel agnostic detection of television advertisements includes normalizing each frame of a video corresponding to broadcast media content on the channel. The method also includes deriving one or more characteristics corresponding to one or more features. The method also includes trimming a pre-defined percentage of area in each frame of the media content based on the one or more characteristics corresponding to the one or more features associated with the media content. The method also includes extracting a first set of audio fingerprints and a first set of video fingerprints. The first set of audio fingerprints and the first set of video fingerprints correspond to a media content broadcasting on the channel. The method also includes detecting the one or more advertisements broadcast across the plurality of channels in the real time.