Residual frame

About: Residual frame is a research topic. Over the lifetime, 4443 publications have been published within this topic receiving 68784 citations.

Method of estimating motion in interlaced video

Abstract: A method of estimating motion in interlaced video involves, firstly, a frame search ( 61 ), where a search is conducted for the frame structure using a sub-sampled block matching metric (e.g. sub-sampled SAD). The locations to be searched are either fixed or dynamically determined based on the minimum frame SAD (ie best frame block match). Next, pixel errors are calculated ( 62 ) for all pixels included in the sub-sampled block matching metric. Each pixel error is first identified as belonging to one of four field patterns (e.g. even-even, even-odd, odd-even and odd-odd). For each location, pixel errors can be classified into two field patterns, either even-even and odd-odd or even-odd and odd-even ( 63 ). The pixel errors belonging to the same field pattern are added together ( 64 ) to obtain field error values (eg field SAD values). The individual field error (or field SAD) values are used to determine ( 77-80 ) the field Motion Vectors. The location of the lowest field SAD value is taken as the position of best match. All pixel errors are then summed together ( 65 ) to obtain the frame error and the location of the lowest frame error (or frame SAD) is taken as the position of best match for the frame. The frame and field Motion Vectors can be refined by using a full block matching metric within the small search window ( 66, 73-76 ).

An Efficient Coding Scheme for Surveillance Videos Captured by Stationary Cameras

Abstract: In this paper, a new scheme is presented to improve the coding efficiency of sequences captured by stationary cameras (or namely, static cameras) for video surveillance applications. We introduce two novel kinds of frames (namely background frame and difference frame) for input frames to represent the foreground/background without object detection, tracking or segmentation. The background frame is built using a background modeling procedure and periodically updated while encoding. The difference frame is calculated using the input frame and the background frame. A sequence structure is proposed to generate high quality background frames and efficiently code difference frames without delay, and then surveillance videos can be easily compressed by encoding the background frames and difference frames in a traditional manner. In practice, the H.264/AVC encoder JM 16.0 is employed as a build-in coding module to encode those frames. Experimental results on eight in-door and out-door surveillance videos show that the proposed scheme achieves 0.12 dB~1.53 dB gain in PSNR over the JM 16.0 anchor specially configured for surveillance videos.

Moving image signal encoding- and decoding apparatus

Abstract: A moving image signal encoding apparatus comprises a frame decimating circuit for extracting encoded frames from an input moving image signal at specified intervals, a frame interpolating circuit for obtaining an interpolated frame between the encoded frames, and a circuit for obtaining an error formed by frame interpolation. A moving image signal decoding apparatus comprises a receiving circuit for extracting a frame code from an inputted signal, a frame decoding circuit for decoding the frame code to obtain a reproduced frame, and a frame interpolating circuit for obtaining an interpolated frame between the reproduced frames. By transmitting an error of the interpolated frame from the encoding apparatus to the decoding apparatus and correcting the error of the interpolated frame with the decoding apparatus, the error of the interpolated frame is eliminated. Alternatively, depending on the value of the error of the interpolated frame obtained with the encoding apparatus, circuit determines the operation mode as to whether the frame interpolating circuit of the decoder carries out frame interpolation or preceding value holding and sends a flag to show the operation mode to the decoder, so that improvement is given when the error of the interpolated frame is large.

Reduced-memory video decoder for compressed high-definition video data

Abstract: A video decoder (30) for decoding compressed high-definition video data (22). The video decoder (30) includes a down-converter (46) and an up-converter (48) placed in the decoder's (30) data path to reduce the amount of video data (22) that needs to be stored in frame buffer memory (40). Reference frame video data is decimated and low-pass filtered by the down-converter (46) for storage in a frame buffer memory (40). The up-converter (48) uses interpolation and low-pass with high boost filtering (82) to reconstruct the reference frames on-the-fly for use in motion compensated prediction.

Frame rate up-conversion using perspective transform

Abstract: In this paper, we propose a frame rate up-conversion (FRUC) algorithm to increase the temporal resolution of video sequences at the decoder side. First, the proposed algorithm segments a frame into several objects. Then, perspective transforms are used to motion-compensate each object, while the translational block matching algorithm (BMA) is applied to the background. Furthermore, the overlapped block motion compensation (OBMC) technique is used to reduce blocking artifacts in boundary blocks. Experimental results show that the proposed algorithm provides better performance than the conventional approach.