Dynamic time warping

About: Dynamic time warping is a research topic. Over the lifetime, 6013 publications have been published within this topic receiving 133130 citations.

Online signature verification using segment-level fuzzy modelling

Abstract: This study presents a new online signature verification system based on fuzzy modelling of shape and dynamic features extracted from online signature data. Instead of extracting these features from a signature, it is segmented at the points of geometric extrema followed by the feature extraction and fuzzy modelling of each segment thus obtained. A minimum distance alignment between the two samples is made using dynamic time warping technique that provides a segment to segment correspondence. Fuzzy modelling of the extracted features is carried out in the next step. A user-dependent threshold is used to classify a test sample as either genuine or forged. The accuracy of the proposed system is evaluated using both skilled and random forgeries. For this, several experiments are carried out on two publicly available benchmark databases, SVC2004 and SUSIG. The experimental results obtained on these databases demonstrate the effectiveness of this system.

Guided time warping for motion editing

Abstract: Time warping allows users to modify timing without affecting poses. It has many applications in animation systems for motion editing, such as refining motions to meet new timing constraints or modifying the acting of animated characters. However, time warping typically requires many manual adjustments to achieve the desired results. We present a technique which simplifies this process by allowing time warps to be guided by a provided reference motion. Given few timing constraints, it computes a warp that both satisfies these constraints and maximizes local timing similarities to the reference. The algorithm is fast enough to incorporate into standard animation workflows. We apply the technique to two common tasks: preserving the natural timing of motions under new time constraints and modifying the timing of motions for stylistic effects.

Real Time Gait Recognition System Based on Kinect Skeleton Feature

Abstract: Gait recognition is a kind of biometric feature recognition technique, which utilizes the pose of walking to recognize the identity Generally people analyze the normal video data to extract the gait feature These days, some researchers take advantage of Kinect to get the depth information or the position of joints for recognition This paper mainly focus on the length of bones namely static feature and the angles of joints namely dynamic feature based on Kinect skeleton information After preprocessing, we stored the two kinds of feature templates into database which we established for the system For the static feature, we calculate the distance with Euclidean distance, and we calculated the distance in dynamic time warping algorithm (DTW) for the dynamic distance We make a feature fusion for the distance between the static and dynamic At last, we used the nearest neighbor (NN) classifier to finish the classification, and we got a real time recognition system and a good recognition result

Shape-based template matching for time series data

Abstract: Dynamic time warping (DTW) distance has been proven to be one of the most accurate distance measures for time series classification. However, its calculation complexity is its own major drawback, especially when a massive training database has to be searched. Although many techniques have been proposed to speed up the search including indexing structures and lower bounding functions, for large databases, it is still untenable to embed the algorithm and search through the entire database of a system with limited resources, e.g., tiny sensors, within a given time. Therefore, a template matching is a solution to efficiently reduce storage and computation requirements; in other words, only a few time series sequences have to be retrieved and compared with an incoming query data. In this work, we propose a novel template matching framework with the use of DTW distance, where a shape-based averaging algorithm is utilized to construct meaningful templates. Our proposed framework demonstrates its utilities, where classification time speedup is in orders of magnitude, while maintaining good accuracy to rival methods.

Dynamic Time Warping Based Static Hand Printed Signature Verification

Abstract: Static signature verication has a signicant use in establishing the authenticity of bank checks, insurance and legal documents based on the signatures they carry. As an individual signs only a few times on the forms for opening an account with any bank or for insurance related purposes, the number of genuine signature templates available in banking and insurance applications is limited, a new approach of static handwritten signature verication based on Dynamic Time Warping (DTW) by using only ve genuine signatures for training is proposed in this paper. Initially the genuine and test signatures belonging to an individual are normalized after calculating the aspect ratios of the genuine signatures. The horizontal and vertical projection features of a signature are extracted using discrete Radon transform and the two vectors are combined to form a combined projection feature vector. The feature vectors of two signatures are matched using DTW algorithm. The closed area formed by the matching path around the diagonal of the DTW-grid is computed and is multiplied with the dierence cost between the feature vectors. A threshold is calculated for each genuine sample during the training. The test signature is compared with each genuine sample and a matching score is calculated. A decision to accept or reject is made on the average of such scores. The entire experimentations were performed on a global signature database (GPDS-Signature Database) of 2106 signatures with 936 genuine signatures and 1170 skilled forgeries. To evaluate the performance, experiments were carried out with 4 to 5 genuine samples for training and with dierent ‘scores’. The proposed as well as the existing DTW-method were implemented and compared. It is observed that the proposed method is superior in terms of Equal Error Rate (EER) and Total Error Rate (TER) when 4 or 5 genuine signatures were used for training. Also it is observed that the False Acceptance Rate (FAR) of the proposed system decreases as the number of genuine training samples increases.