The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We propose mutually incoherent pose bases for action recognition in static image, each of which implicitly represents co-occurrence of poselets. First of all, action specific poselets are trained. To suppress the ambiguity of detection, we cluster poselet activations by the overlap of predicted torso bound of each poselet. Then pose feature of an action person can be extracted which is a vector composed...
In this article we present CoSC, a generic framework for collaborative segmentation and classification. The framework is guided by both radiometric homogeneity based criteria and implicit semantic criteria to segment and extract the objects of a given thematic class. We present a proof-of-concept case-study and show that CoSC is able to reach higher confidence for object classification and results...
Surveillance cameras have become big business, with most metropolitan cities spending millions of dollars to watch residents, both from street corners, public transportation hubs, and body cameras on officials. Watching and processing the petabytes of streaming video is a daunting task, making automated and user assisted methods of searching and understanding videos critical to their success. Although...
Content based indexing is critical to the effective access of the multimedia data. To this end, visual data is often annotated with textual content for bridging the semantic gap. In this paper, we present a method to generate frame level fine grained annotations for a given video clip. Access to the frame level fine grained annotations lead to rich, dense and meaningful semantic associations between...
Image annotation is a hard multi-label learning problem which aims at automatically tagging each input image with relevant keywords reflecting its semantic concepts. Recently, several late fusion methods were proposed to improve the accuracy of image annotation. But these late fusion methods need normalization of confidence score vectors of independent models corresponding to distinct representations...
Image registration is an important and fundamental problem in computer vision and image processing. Although there are currently a large number of image registration algorithms such as RANSAC and its extensions, image registration under very noisy conditions remains difficult when it cannot obtain enough number of correct corresponding points. This paper solves this issue by introducing a random resample...
Road detection from images is a challenging task in computer vision. Previous methods are not robust, because their features and classifiers cannot adapt to different circumstances. To overcome this problem, we propose to apply unsupervised feature learning for road detection. Specifically, we develop an improved encoding function and add a feature selection process to obtain robust and discriminative...
Glare is a hardware problem that occurs because of the light trapped in the lens elements. It is a common problem faced in photography when trying to capture image of a scene having bright source in it or taken in a very bright environment. Glare can hide useful information in the image, can make foreground objects blurry and deformed. In this paper, we propose a novel method to detect glare, mainly...
Video skimming is a process of generating a shorter yet fully comprehensible version of a given video as its dynamic summary. A generic skimming system involves division of the video into segments and selecting the segments based on their suitability. The suitability is often obtained considering various features of the video and combining their individual contributions. Suggesting that the combination...
This paper presents a prediction based spatio-temporal seam carving scheme for video retargeting. It resizes the video maintaining appropriate balance between spatial and temporal coherence. In a video frame, the proposed approach finds a ‘temporal’ seam by using Kalman filter estimation and then modifies it with the help of ‘spatial’ seam considering both spatial and temporal coherency. Unlike image...
To avoid the introduction of false information during the fusion progress, a novel multi-focus image fusion method is proposed in quaternion wavelet transform domain. To obtain the dependency in different high frequency subbands, a quaternion wavelet contextual hidden Markov model (Q-CHMM) is established for modeling quaternion wavelet coefficients. And for better image representations, several features...
Gait recognition has been proved useful in human identification at a distance. But view variance of gait feature is always a great challenge because of the difference in appearance. If the view of the probe is different from that of the gallery, one view transformation model can be employed to convert the gait feature from one view to another. But most existing models need to estimate the view angle...
The analysis of human gait is more and more investigated due to its large panel of potential applications in various domains, like rehabilitation, deficiency diagnosis, surveillance and movement optimization. In addition, the release of depth sensors offers new opportunities to achieve gait analysis in a non-intrusive context. In this paper, we propose a gait analysis method from depth sequences by...
In the field of gait recognition from motion capture data, designing human-interpretable gait features is a common practice of many fellow researchers. To refrain from ad-hoc schemes and to find maximally discriminative features we may need to explore beyond the limits of human interpretability. This paper contributes to the state-of-the-art with a machine learning approach for extracting robust gait...
Large vocabulary gesture recognition using a training set of limited size is a challenging problem in computer vision. With few examples per gesture class, researchers often employ exemplar-based methods such as Dynamic Time Warping (DTW). This paper makes two contributions in the area of exemplar-based gesture recognition: 1) it introduces Multiple-Pass DTW (MP-DTW), a method in which scores from...
Modeling the relationship among human joints is one of the most important components in human pose estimation. Previous methods usually define this relationship as geometric constraints on the relative location of two neighboring joints. In this definition, the local image appearance of the region connecting two neighboring joints is ignored. In fact, this image appearance, called human limb, plays...
With the availability of the recent human skeleton extraction algorithm introduced by Shotton et al. [1], an interest for skeleton-based action recognition methods has been renewed. Despite the importance of the low-latency aspect in applications, it can be noted that the majority of recent approaches has not been evaluated in terms of computational cost. In this paper, a novel fast and accurate human...
Automatic analysis of rodent behavior has been receiving growing attention in recent years since rodents have been the reference species for many neuroscientific studies, with the social interaction being among the subjects of the most important ones. Systems that are employed in these studies are mainly based on tracking of mice and activity classification through supervised learning methods, trained...
Fingerprint classification is an effective technique for reducing the candidate numbers of fingerprints in the stage of matching in automatic fingerprint identification system (AFIS). In recent years, deep learning is an emerging technology which has achieved great success in many fields, such as image processing, computer vision. In this paper, we have a preliminary attempt on the traditional fingerprint...
Orientation Field (OF) is one of the most significant characters to distinguish fingerprint images from non-fingerprint images. An effective definition of fingerprint OF pattern will not only benefit fingerprint enhancement, but also contribute to latent fingerprint detection and segmentation. The existing fingerprint OF models either require pre-knowledge of singular points, or cannot be generalized...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.