Seungjae Lee

Audio fingerprinting based on normalized spectral subband moments

The performance of a fingerprinting system, which is often measured in terms of reliability and robustness, is directly related to the features that the system uses. In this letter, we present a new audio-fingerprinting method based on the normalized spectral subband moments. A threshold used to reliably determine a fingerprint match is obtained by modeling the features as a stationary process. The robustness of the normalized moments was evaluated experimentally and compared with that of the spectral flatness measure. Among the considered subband features, the first-order normalized moment showed the best performance for fingerprinting.

Audio fingerprinting based on normalized spectral subband centroids

For multimedia fingerprinting, it is crucial to extract relevant features that allow direct access to the distinguishing characteristics of a multimedia object. Features used for fingerprinting directly relate to the performance of the entire fingerprinting system. The paper proposes a novel audio fingerprinting method based on normalized spectral subband centroids. The spectral subband centroid is selected due to its resilience against equalization, compression, and noise addition. Both reliability and robustness issues in the fingerprinting system are addressed. Experimental results show that the proposed method is not only reliable, but also robust against various audio processing steps, including MP3 compression, equalization, random start, time-scale modification, and linear speed change.

An SVD-based watermarking method for image content authentication with improved security

For image content authentication, a secure watermarking method using quantization-based embedding on the largest singular value (SV) is proposed. The block-wise quantization-based embedding can be vulnerable to vector quantization (VQ) attack and attacks associated with histogram analysis. To overcome these security problems, the proposed method places interdependency among image blocks and dithers the quantized value. By adjusting the threshold of the detector, a trade-off between the robustness to JPEG compression and the probability of misdetection can be made. The proposed method can detect a tampered area with high sensitivity. This is confirmed by experimental results and security analysis.

Fast communication: Higher-order moments for musical genre classification

This paper presents a study on the performance of the higher-order moments for musical genre classification. Especially the skewness and the kurtosis of the octave-scale subbands are considered. Experimental results on the widely used music datasets show that the higher-order moment features can improve classification accuracy when combined with the conventional lower-order moment features.

Video fingerprinting based on orientation of luminance centroid

In this paper, we propose a video fingerprinting method based on the orientation of luminance centroid. To attain robustness against frame rate change, variation in color characteristics and resizing, video frames are normalized in time, spatial and color domain. Thereafter, the orientation of luminance centroid is calculated as as video fingerprint. Under various distortions, the proposed method is evaluated and compared with other centroid-based methods. Experimental results show that the proposed method satisfies the requirements of video fingerprint, and performance comparison with other methods in terms of receiver operating characteristic indicates that the proposed method is more robust and has better discriminatory property than others.

Robust video fingerprinting based on hierarchical symmetric difference feature

The piracy of copyrighted digital content over the Internet infringes copyrights and damages the digital content industry. Accordingly, identifying and monitoring technology on the online content service like fingerprinting is getting valuable through the explosion of digital content sharing. This paper proposes a robust video fingerprinting feature to identify a modified video clip from a large scale database. Hierarchical symmetric difference feature is proposed in order to offer efficient video fingerprinting. The feature is robust and pairwise independent against various video modifications such as compression, resizing, or cropping. Moreover, videos undergoing a transformation such as flipping or mirroring can be identified by simply disordering the bit pattern of fingerprints. The performance of the proposed feature is extensively experimented on 6,482 hours of database and the experimental results show that the proposed fingerprinting is efficient and robust against various modifications.

Extensive analysis of feature selection for compact descriptor

In this paper, feature selection criteria of local descriptors are examined with well-defined evaluation framework in MPEG-7 compact descriptor for visual search (CDVS) [6]. The effect of feature selection on descriptor was analyzed in compressed and uncompressed domain. Various combinations of feature characteristics such as scale and orientation of features, distance from center, and response of difference of Gaussian (DoG) [5] were examined for feature selection criterion via pair-wise matching experiments in MPEG-7 CDVS datasets.

Smoodi: Mood-based music recommendation player

In this paper, we present a mood-based music recommendation player: Smoodi. The Smoodi provides smart mood recommendation by touch and drag and it has three different views: Mood Square, Cover Flow and Mood Cloud. In the Mood Square, users can check the mood distribution of local clips and generate playlists by touching mood cells. In the Cover Flow, users can find music information and generate similar songs list by dragging a seed song. In the Tag Cloud, users can make playlists by selecting mood tags. For this application, we developed new mood model from collected mood tags and arousal-valence position values and designed a regression function to estimate mood probabilities.

A TV commercial monitoring system using audio fingerprinting

In this paper, we describe an audio fingerprinting-based commercial monitoring system for TV broadcasting. The goal of the commercial monitoring is to identify commercials being broadcasted and find out the time duration. If there are similar commercials in the fingerprint database, we sometimes have trouble in determining which commercial has been broadcasted. To solve this problem, we propose the partial distance comparison method which identifies commercials and discriminates them from background music. Experimental results show that the proposed method improves commercial-identification performance by discriminating different versions of the same commercial.

Arm Trajectory Generation Based on RRT* for Humanoid Robot

In this paper, an arm trajectory generation method based on the Rapidly-Exploring Random Tree Star (RRT*) is proposed for humanoid robot. The RRT* is one of anytime motion planning algorithms. The RRT* adopts the three fundamental components from the RRT, the preceding version of RRT*: the state variables, local planner, and cost function. The end effector of humanoid robot is positioned on the desired point by manipulating the joint angles of the arm, which are the state variables. The Minimum-jerk method is applied as a local planner for more realistic trajectory and the local planner fulfills collision detection test. The cost taken to transit between two points is defined as the sum of angle differences of motor corresponding to the two points. Also, there has been the need for real time control and it is taken care of by introducing a multi-thread system. The arm under control initiates motioning, once the first trajectory that meets the target zone is constructed. While the arm is on the move, the RRT* continuously updates the trajectory. The effectiveness of the proposed method is demonstrated by simulating the 7 DOF robot arm, which has been performed under two environments: the obstacle-free and obstacle-constrained cases. Simulation is carried out for the humanoid robot, Mybot-KSR, developed in the RIT Lab., KAIST.