Real-time pulse rate (PR) monitoring based on photoplethysmography (PPG) has been drawn much attention in recent years. However, PPG signal detected under movement is easily affected by random noises, especially motion artifacts (MA), affecting the accuracy of PR estimation. In this paper, a parallel method structure is proposed, which effectively combines wavelet threshold denoising with recursive least squares (RLS) adaptive filtering to remove interference signals, and uses spectral peak tracking algorithm to estimate real-time PR. Furthermore, we propose a parallel structure RLS adaptive filtering to increase the amplitude of spectral peak associated with PR for PR estimation. This method is evaluated by using the PPG datasets of the 2015 IEEE Signal Processing Cup. Experimental results on the 12 training datasets during subjects' walking or running show that the average absolute error (AAE) is 1.08 beats per minute (BPM) and standard deviation (SD) is 1.45 BPM. In addition, the AAE of PR on the 10 testing datasets during subjects' fast running accompanied with wrist movements can reach 2.90 BPM. Furthermore, the results indicate that the proposed approach keeps high estimation accuracy of PPG signal even with strong MA.

In this letter, methods of inactive regions padding for Segmented Sphere Projection (SSP) of 360 videos are proposed. A 360 video is projected onto a 2D plane to be coded with diverse projection formats. Some projection formats have inactive regions in the converted 2D plane such as SSP. The inactive regions may cause visual artifacts as well as coding efficiency decrease due to discontinuous boundaries between active and inactive regions. In this letter, to improve coding efficiency and reduce visual artifacts, the inactive regions are padded by using two types of adjacent pixels in either rectangular-face or circle-face boundaries. By padding the inactive regions with the highly correlated adjacent pixels, the discontinuities between active and inactive regions are reduced. The experimental results show that, in terms of end-to-end Weighted to Spherically uniform PSNR (WS-PSNR), the proposed methods achieve 0.3% BD-rate reduction over the existing padding method for SSP. In addition, the visual artifacts along the borders between discontinuous faces are noticeably reduced.

In this paper, we propose a spatially adaptive gradient-projection algorithm for the H.264 video coding standard to remove coding artifacts using local statistics. A hybrid method combining a new weighted constrained least squares (WCLS) approach and the projection onto convex sets (POCS) approach is introduced, where weighting components are determined on the basis of the human visual system (HVS) and projection set is defined by the difference between adjacent pixels and the quantization index (QI). A new visual function is defined to determine the weighting matrices controlling the degree of global smoothness, and a projection set is used to obtain a solution satisfying local smoothing constraints, so that the coding artifacts such as blocking and ringing artifacts can be simultaneously removed. The experimental results show the capability and efficiency of the proposed algorithm.

This paper proposes an improved method that uses a K-means method to effectively reduce the ringing artifacts in a color moving picture. To apply this improved K-method, we set the number of groups for the process to two (K=2) in the three dimensional R, G, B color space. We then improved the R, G, B color value of all of the pixels by moving the current R, G, B color value of each pixel to calculated center values, which reduced the ringing artifacts. The results were verified by calculating the overshoot and the slope of the light luminance around the edges of test images that had been processed by the new algorithm. We then compared the calculated results with the overshoot and slope of the light luminance of the unprocessed image.

In the acquisition of projection data of X-ray CT, logarithm operation is indispensable. But noise distribution is nonlinearly projected by the logarithm operation, and this deteriorates the precision of CT number. This influence becomes particularly remarkable when only a few photons are caught with a detector. It generates a strong streak artifact (SA) in a reconstructed image. Previously we have clarified the influence of the nonlinearity by statistical analysis and proposed a correction method for such nonlinearity. However, there is a problem that the compensation for clamp processing cannot be performed and that the suppression of SA is not enough in photon shortage state. In this paper, we propose a new technique for correcting the nonlinearity due to logarithm operation for noisy data by combining the previously presented method and an adaptive filtering method. The technique performs an adaptive filtering only when the number of captured photons is very few. Moreover we quantitatively evaluate the influence of noise on the reconstructed image in the proposed method by the experiment using numerical phantoms. The experimental results show that there is less influence on spatial resolution despite suppressing SA effectively and that CT number are hardly dependent on the number of the incident photons.

Based on the theory of block projection onto convex sets (BPOCS), a novel de-blocking algorithm is proposed. A new smoothness constraint set (SCS) is used to remove the unnecessary high frequencies. In addition, an adaptive quantization constraint set (AQCS) is employed to suppress error in the smoothing process. The proposed size and position of new SCS are different from traditional ones. Extensive experimental results are provided to demonstrate that the proposed method can achieve better image quality with fewer iterations.

We describe attempts to have robots behave as embodied knowledge media that will permit knowledge to be communicated through embodied interactions in the real world. The key issue here is to give robots the ability to associate interactions with information content while interacting with a communication partner. Toward this end, we present two contributions in this paper. The first concerns the formation and maintenance of joint intention, which is needed to sustain the communication of knowledge between humans and robots. We describe an architecture consisting of multiple layers that enables interaction with people at different speeds. We propose the use of an affordance-based method for fast interactions. For medium-speed interactions, we propose basing control on an entrainment mechanism. For slow interactions, we propose employing defeasible interaction patterns based on probabilistic reasoning. The second contribution is concerned with the design and implementation of a robot that can listen to a human instructor to elicit knowledge, and present the content of this knowledge to a person who needs it in an appropriate situation. In addition, we discuss future research agenda toward achieving robots serving as embodied knowledge media, and fit the robots-as-embodied-knowledge-media view in a larger perspective of Conversational Informatics.

In this paper, we introduce a low computing post processing algorithm to simultaneously suppress blocking and ringing artifacts of compressed video sequences. A new regularization function to incorporate smoothness to neighboring pixels is defined, where the function is composed of four sub-functions combined with pixel-based data fidelity and smoothing terms. Therefore, the solution can be obtained without inverse matrix or vector-matrix computation, so that low complexity implementation is possible. In addition, the regularization parameter controlling the relative importance between the data fidelity and the degree of smoothness is estimated from the available overhead information in decoder, such as, macroblock type and quantization step size. The experimental results show the capability and efficiency of the proposed algorithm.

This paper proposes an effective JPEG 2000 encoding method for reducing tiling artifacts, which cause one of the biggest problems in JPEG 2000 encoders. Symmetric pixel extension is generally thought to be the main factor in causing artifacts. However this paper shows that differences in quantization accuracy between tiles are a more significant reason for tiling artifacts at middle or low bit rates. This paper also proposes an algorithm that predicts whether tiling artifacts will occur at a tile boundary in the rate control process and that locally improves quantization accuracy by the original post quantization control. This paper further proposes a method for reducing processing time which is yet another serious problem in the JPEG 2000 encoder. The method works by predicting truncation points using the entropy of wavelet transform coefficients prior to the arithmetic coding. These encoding methods require no additional processing in the decoder. The experiments confirmed that tiling artifacts were greatly reduced and that the coding process was considerably accelerated.

A novel postprocessing algorithm for reducing the blocking artifacts in block-based coded images is proposed using block classification and adaptive multi-layer perceptron (MLP). This algorithm is exploited the nonlinearity property of the neural network learning algorithm to reduce the blocking artifacts more accurately. In this algorithm, each block is classified into four classes; smooth, horizontal edge, vertical edge, and complex blocks, based on the characteristic of their discrete cosine transform (DCT) coefficients. Thereafter, according to the class information of the neighborhood block, adaptive neural network filters (NNF) are then applied to the horizontal and vertical block boundaries. That is, for each class a different two-layer NNF is used to remove the blocking artifacts. Experimental results show that the proposed algorithm produced better results than conventional algorithms both subjectively and objectively.

The performance of AC plasma displays has been improved in the area of brightness and contrast, while significant advances in image quality are still required for the HDTV quality. In particular, in full color motion video, motion artifacts and lack of color depth are still visible in some situations. These motional artifacts are mitigated as the number of the subfields increases, usually at the cost of losing brightness or increasing driving circuitry. Therefore, it is still one of our great concerns to find out the optimized subfield configuration through weighting and order of each subfield, and their coding of combination. For evaluation and improvement of motion picture disturbance, we have established a procedure that fully simulates the image quality of displays which utilize the subfield driving scheme. The simulation features virtually located sensor pixels on human retina, eye-tracking sensor windows, and a built-in spatial low pass filter. The model pixelizes the observers retina like a sensor chip in a CCD camera. An eye-tracking sensor window is assigned to every light emission from the display, to calculate the emissions from one to four adjoining pixels along the trajectory of motion. Through this model, a scene from original motion picture without disturbance is transformed into the still image with simulated disturbance. The integration of the light emission from adjoining pixels through the window, also functions as a built-in spatial low pass filter to secure the robust output, considering the MTF of the human eye. Both simulation and actual 42-in-diagonal PDPs showed close results under various conditions, showing that the model is simple, but reasonable. Through the simulation, general properties of the subfield driving scheme for gray scale have been elucidated. For example, a PWM-like coding offers a better performance than an MSB-split coding in many cases. The simulation also exemplifies the motion picture disturbance as a non-linear filter process caused by the dislocation of bit weightings, suggesting that tradeoffs between disturbance and resolution in motion area are mandatory.