• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.693-700
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• 2012

The effective extraction of key frames from a video stream is an essential task for summarizing and representing the content of a video. Accordingly, this paper proposes a new and fast method for extracting key frames from a compressed video. In the proposed approach, after the entire video sequence has been segmented into elementary content units, called shots, key frame extraction is performed by first assigning the number of key frames to each shot, and then distributing the key frames over the shot using a probabilistic approach to locate the optimal position of the key frames. The main advantage of the proposed method is that no time-consuming computations are needed for distributing the key frames within the shots and the procedure for key frame extraction is completely automatic. Furthermore, the set of key frames is independent of any subjective thresholds or manually set parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4533-4551
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• 2014

The effective extraction of key frames from a video stream is an essential task for summarizing and representing the content of a video. Accordingly, this paper proposes a new and fast method for extracting key frames from a compressed video. In the proposed approach, after the entire video sequence has been segmented into elementary content units, called shots, key frame extraction is performed by first assigning the number of key frames to each shot, and then distributing the key frames over the shot using a probabilistic approach to locate the optimal position of the key frames. Moreover, we implement our proposed framework in Android to confirm the validity, availability and usefulness. The main advantage of the proposed method is that no time-consuming computations are needed for distributing the key frames within the shots and the procedure for key frame extraction is completely automatic. Furthermore, the set of key frames is independent of any subjective thresholds or manually set parameters.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.137-140
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• 2000

In this paper, we propose as new algorithm for the selection of key frames in a given video. For the selected key frames to be well defined, the selected key frames need to spread out on the whole temporal domain of the given video and guaranteed not to be duplicate. For this purpose, we take the first frame of each shot of the video as the candidate key frame to represent the video. To reduce the overall processing time, we eliminate some candidate key frames which are visually indistinct in the histogram difference. The key frames are then selected using a clustering processing based on the singly linked hierarchical tree. To make the selected key frames be distributed evenly on the whole video, the deviation and time difference between the selected key frames are used. The simulation results demonstrate that our method provides the better performance compared with previous methods.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.1-9
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• 2016

In order to reconstruct a 3D model in video sequences, to select key frames that are easy to estimate a geometric model is essential. This paper proposes a method to easily extract informative frames from a handheld video. The method combines selection criteria based on appropriate-baseline determination between frames, frame jumping for fast searching in the video, geometric robust information criterion (GRIC) scores for the frame-to-frame homography and fundamental matrix, and blurry-frame removal. Through experiments with videos taken in indoor space, the proposed method shows creating a more robust 3D point cloud than existing methods, even in the presence of motion blur and degenerate motions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.1
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• pp.43-50
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• 2009

This paper caters the need of acquiring the principal objects, characters, and scenes from a video in order to entertain the image based query. The movie frames are divided into frames with 2D representative images called "key frames". Various regions in a key frame are marked as key objects according to their textures and shapes. These key objects serve as a catalogue of regions to be searched and matched from rest of the movie, using viewpoint invariant regions calculation, providing the location, size, and orientation of all the objects occurring in the movie in the form of a set of structures collaborating as video profile. The profile provides information about occurrences of every single key object from every frame of the movie it exists in. This information can further ease streaming of objects over various network-based viewing qualities. Hence, the method provides an effective reduced profiling approach of automatic logging and viewing information through query by example (QBE) procedure, and deals with video streaming issues at the same time.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.595-604
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• 2013

Currently, registered number of imported vehicles is increasing rapidly over the years. Accordingly, environment improvements of vehicle maintenance company for maintenance of luxury vehicle such as imported vehicle are continuously being made. In this paper, we propose a key frame extraction method based on HSV color model for smart vehicle management system implementation to offer for customer reliability of maintenance vehicle. After automatically recognize the license plates of the vehicle using vehicle license plate recognition system when the vehicle come in the car center, we check the repair history and request of the vehicle based on it. We implement mobile services which provide extracted key frame images to the user after extract key frames from vehicle repair video. In addition, we verify the superiority of key frame extraction method by applying a smart vehicle management system. Finally, we convert the RGB color to HSV color to improve the performance of proposed key frame extraction scheme. As a result, we confirmed that our scheme is more excellence about 30% in terms of recall than RGB color model from the performance evaluations.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.179-182
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• 2001

In this paper. a key frame extraction algorithm for browsing and searching the summary of a video is proposed. Toward this end, important frames representing a shot are selected according to the correlations among frames. by using the Fourier descriptor which is useful for the shot boundary detection. To quantitatively evaluate the importance of selected frames. a new measure based on correlation coefficients of frames is proposed. If there are several frames with a same importance. another criteria is introduced to break the tie. by computing the partial moment of subframes including each candidate key frame so that the distortion rate is minimized Since a key frame extraction algorithm can be evaluated subjectively. the performance of the proposed algorithm has been verified by a statistical test. Experiments show that more than 20% improvement has been obtained by the proposed algorithm compared to existing methods.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.457-469
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• 2003

In this paper, we have proposed the efficient algorithm that can segment the video scene change using a various statistical characteristics obtained from by applying the wavelet transformation for each frames. Our method firstly extracts the histogram features from low frequency subband of wavelet-transformed image and then uses these features to detect the abrupt scene change. Second, it extracts the edge information from applying the mesh method to the high frequency subband of transformed image. We quantify the extracted edge information as the values of variance characteristic of each pixel and use these values to detect the gradual scene change. And we have also proposed an algorithm how extract the proper key frame from segmented video scene. Experiment results show that the proposed method is both very efficient algorithm in segmenting video frames and also is to become the appropriate key frame extraction method.

• Journal of Korea Game Society
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• v.16 no.4
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• pp.97-104
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• 2016

This study suggests a technique to implement the production of animation by blending between key frame animation and motion capture animation through short animation 'Drip.' It reduced the time taken to produce an animation by not only enabling efficient process management through mutual organic connection but also conducting a process of mutually making up for weak points of key frame animation and motion capture animation. Through this, it was intended to be helpful in efficient animation production by overcoming the limitation of key frame animation and motion capture animation and perceiving and applying a complex process.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.501-504
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• 2003

In this out watermarking method, a key is determined by quantizing the maximum motion difference between frames. We have a problem the key value for embedding and detection are different in 1 to 3% frames of all frames. This problem can be easily solved by using a new key according to bit error rate of the extracted watermark. Since the watermark is embedded in each frame nth different keys and detected In all the frames, out method is resistant against attacks such as the frame averaging and frame drop.