Homer H. Chen

A Regression Approach to Music Emotion Recognition

Content-based retrieval has emerged in the face of content explosion as a promising approach to information access. In this paper, we focus on the challenging issue of recognizing the emotion content of music signals, or music emotion recognition (MER). Specifically, we formulate MER as a regression problem to predict the arousal and valence values (AV values) of each music sample directly. Associated with the AV values, each music sample becomes a point in the arousal-valence plane, so the users can efficiently retrieve the music sample by specifying a desired point in the emotion plane. Because no categorical taxonomy is used, the regression approach is free of the ambiguity inherent to conventional categorical approaches. To improve the performance, we apply principal component analysis to reduce the correlation between arousal and valence, and RReliefF to select important features. An extensive performance study is conducted to evaluate the accuracy of the regression approach for predicting AV values. The best performance evaluated in terms of the R 2 statistics reaches 58.3% for arousal and 28.1% for valence by employing support vector machine as the regressor. We also apply the regression approach to detect the emotion variation within a music selection and find the prediction accuracy superior to existing works. A group-wise MER scheme is also developed to address the subjectivity issue of emotion perception.

Programmable aperture photography: multiplexed light field acquisition

In this paper, we present a system including a novel component called programmable aperture and two associated post-processing algorithms for high-quality light field acquisition. The shape of the programmable aperture can be adjusted and used to capture light field at full sensor resolution through multiple exposures without any additional optics and without moving the camera. High acquisition efficiency is achieved by employing an optimal multiplexing scheme, and quality data is obtained by using the two post-processing algorithms designed for self calibration of photometric distortion and for multi-view depth estimation. View-dependent depth maps thus generated help boost the angular resolution of light field. Various post-exposure photographic effects are given to demonstrate the effectiveness of the system and the quality of the captured light field.

Error-resilient coding in JPEG-2000 and MPEG-4

The rapid growth of mobile communications and the widespread access to information via the Internet have resulted in a strong demand for robust transmission of compressed image and video data for various multimedia applications and services. The challenge of robust transmission is to protect the compressed image/video data against hostile channel conditions while bringing little impact on bandwidth efficiency. This paper addresses this critical problem and provides an overview of the error-resilient approaches that have been evaluated and inserted into the emerging JPEG-2000 wavelet-based image coding standard. We also review the state-of-the-art techniques adopted in the MPEG-4 standard for robust transmission of video and still texture data. These techniques include resynchronization strategies, data partitioning, reversible VLCs, and header extension codes. The performance of these approaches under various channel conditions is evaluated.

Machine Recognition of Music Emotion: A Review

The proliferation of MP3 players and the exploding amount of digital music content call for novel ways of music organization and retrieval to meet the ever-increasing demand for easy and effective information access. As almost every music piece is created to convey emotion, music organization and retrieval by emotion is a reasonable way of accessing music information. A good deal of effort has been made in the music information retrieval community to train a machine to automatically recognize the emotion of a music signal. A central issue of machine recognition of music emotion is the conceptualization of emotion and the associated emotion taxonomy. Different viewpoints on this issue have led to the proposal of different ways of emotion annotation, model training, and result visualization. This article provides a comprehensive review of the methods that have been proposed for music emotion recognition. Moreover, as music emotion recognition is still in its infancy, there are many open issues. We review the solutions that have been proposed to address these issues and conclude with suggestions for further research.

A screw motion approach to uniqueness analysis of head-eye geometry

The screw motion theory is used to solve a class of pose determination problems that can be characterized by a homogeneous transform equation of the form AX=XB, where A and B are known motions and X is an unknown coordinate transformation. Unlike existing methods, this method gives rise to a sound geometric interpretation that takes both rotation and translation into consideration. The author derives a screw congruence theorem and shows that the problem is to find a rigid transformation which will bring one group of lines to overlap another. He also provides a complete analysis of the conditions under which the solution can be uniquely determined.<<ETX>>

A survey of construction and manipulation of octrees

Abstract The octree representation of three-dimensional objects based on the principle of recursive subdivision is a generalization of two-dimensional quadtrees. It has been studied for use in many application areas such as solid modeling, computer graphics, computer-aided design/manufacturing, computer vision, image processing, and robotics. Many algorithms related to octrees have been developed in these application areas. In this paper, we divide these algorithms into two categories, construction and manipulation of octrees, and give a detailed survey of them.

Music emotion classification: a fuzzy approach

Due to the subjective nature of human perception, classification of the emotion of music is a challenging problem. Simply assigning an emotion class to a song segment in a deterministic way does not work well because not all people share the same feeling for a song. In this paper, we consider a different approach to music emotion classification. For each music segment, the approach determines how likely the song segment belongs to an emotion class. Two fuzzy classifiers are adopted to provide the measurement of the emotion strength. The measurement is also found useful for tracking the variation of music emotions in a song. Results are shown to illustrate the effectiveness of the approach.

Analysis and Compensation of Rolling Shutter Effect

Due to the sequential-readout structure of complementary metal-oxide semiconductor image sensor array, each scanline of the acquired image is exposed at a different time, resulting in the so-called electronic rolling shutter that induces geometric image distortion when the object or the video camera moves during image capture. In this paper, we propose an image processing technique using a planar motion model to address the problem. Unlike previous methods that involve complex 3-D feature correspondences, a simple approach to the analysis of inter- and intraframe distortions is presented. The high-resolution velocity estimates used for restoring the image are obtained by global motion estimation, Bezier curve fitting, and local motion estimation without resort to correspondence identification. Experimental results demonstrate the effectiveness of the algorithm.

Perceptual Rate-Distortion Optimization Using Structural Similarity Index as Quality Metric

The rate-distortion optimization (RDO) framework for video coding achieves a tradeoff between bit-rate and quality. However, objective distortion metrics such as mean squared error traditionally used in this framework are poorly correlated with perceptual quality. We address this issue by proposing an approach that incorporates the structural similarity index as a quality metric into the framework. In particular, we develop a predictive Lagrange multiplier estimation method to resolve the chicken and egg dilemma of perceptual-based RDO and apply it to H.264 intra and inter mode decision. Given a perceptual quality level, the resulting video encoder achieves on the average 9% bit-rate reduction for intra-frame coding and 11% for inter-frame coding over the JM reference software. Subjective test further confirms that, at the same bit-rate, the proposed perceptual RDO indeed preserves image details and prevents block artifact better than traditional RDO.

A block transform coder for arbitrarily shaped image segments

This paper describes a method for coding arbitrarily shaped image segments. The method uses an iterative technique based on the theory of successive projection onto convex sets to determine the best transform coefficients. It uses block transforms with frequency domain region-zeroing and space domain region-enforcing operations for effective coding of image segments of arbitrary shape. A major strength of this method is that it can be implemented in real-time using existing codec hardware at an insignificant additional cost.<<ETX>>