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.
Preventing a traffic accident is a good way to solve many problems in the world for the current generation surrounding with many automotive technologies causing many people's death from the accident. The prevention makes an important impact to every society for making many people more safety and improving their lives' quality. In the fact, the primary cause is mostly drivers' carelessness and lacking...
This paper presents the result of a recent large-scale subjective study of image retargeting quality on a collection of images generated by several representative image retargeting methods. Owning to many approaches to image retargeting that are developed, there is a need for a diverse independent public database of the retargeted images and the corresponding subjective scores that is freely available...
This paper presents a hierarchal, two-layer, connectionist-based human-action recognition system (CHARS) as a first step towards developing socially intelligent robots. The first layer is a K-nearest neighbor (K-NN) classifier that categorizes human actions into two classes based on the existence of locomotion, and the second layer consists of two multi-layer recurrent neural networks that distinguish...
Increased frequency of micronuclei is positively correlated with the molecular dosimetry of genotoxic damages. The cytokinesis-block micronucleus test (CBMN test) is a well-established assay used in toxicological screening for potential genotoxic compounds. Since the method is simple and economical, CBMN assay can be employed on a large scale as a quantitative biological dosimeter. Automated detection...
Pedestrian detection is one of the fundamental tasks of an intelligent transportation system. Differences in illumination, posture and point of view make pedestrian detection confront with great challenges. In this paper, we focus on the main defect in the existing methods: the interference of the non-person area. Firstly, we use mapping vectors to map the original feature matrix to the different...
This paper summarizes the recent development of action recognition at first. Then based on Hierarchical Filtered Motion model and Nearest Neighbor classifier, we do action recognition using HOG feature in video sequences of different resolutions. Here we use KTH dataset for training and MSR action dataset II for testing. The experiment demonstrates that the new feature extraction process is effective...
We have performed city-verification of videos based on the videos' audio and metadata, using videos from the MediaEval Placing Task's video set, which contain consumer-produced videos “from-the-wild”. 18 cities were used as targets, for which acoustic and language models were trained, and against which test videos were scored. We have obtained the first known results for the city verification task,...
In object detection, the offline trained detector's performance may be degraded in a particular deployed environment, because of the large variation of different environments. In this work, we propose a data level object detector adaptation method to new environments. By recording a small amount of offline data, it's fully compatible with offline training method and easy to implement. We re-derive...
In some sport training application, it is necessary to search the key frames of training video for carefully analysis. In this paper, we take the key frame searching issue as a pose estimation problem. First, a set of various pose detectors are collected trough the twice SVM training process, each of which can be interpreted as a learned pose-specific HOG weight classifier. Then we run each linear...
Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate. Then, the system should self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome...
Sparse representation based classification (SRC) has been widely used for face recognition (FR). Although SRC algorithm is also adopted in human action recognition, the evaluations of different regular terms have not been given. In this paper, we will discuss and evaluate the role of different regular terms of SRC in human action recognition, after that, we propose human action recognition algorithm...
We propose an approach to recognize group activities which involve several persons based on modeling the interactions between human bodies. Benefitted from the recent progress in pose estimation [1], we model the activities as the interactions between the parts belong to the same person (intra-person) and those between the parts of different persons (inter-person). Then a unified, discriminative model...
This paper proposes a method for estimating the quantitative values of some attributes associated with surface qualities of an object, such as glossiness and transparency, from its image. Our approach is to learn functions that compute such attribute values from the input image by using training data given in the form of relative information. To be specific, each sample of the training data represents...
The purpose of this paper is to develop an approach to learn dynamic Bayesian network (DBN) discriminatively for human activity recognition. DBN is a generative model widely used for modeling temporal events in human activity recognition. The parameters of the DBN models are usually learned through maximizing likelihood or expected likelihood. However, activity is often recognized through identifying...
This paper investigates the problem of gait-based gender classification in unconstrained environments. Different from existing human gait analysis and recognition methods which assume that humans walk in controlled environments, we aim to recognize human gender from uncontrolled gaits in which people can walk freely and the walking direction of human gaits may be time-varying in a singe video clip...
While the generalizability of classifiers receive much attention in research, interpretability is often neglected. This paper proposes a rule-plus-exemplar classification framework based on ideas in cognitive psychology. The classification process is interpretable and intuitive, and also generalizes well. It can perform better than other interpretable methods such as decision trees, for both interpolative...
Systems developed without addressing subjective experience can generate interactions successful in their tasks but counterproductive as experiences. Addressing subjective experience requires creating hypothetical situations with realistic human actors, subjectivity's embodied nature prevents examination in isolation from either person or context. The Contextual Scenario Framework (CSF) assists in...
Generating realistic test data is a major problem for software testers. Realistic test data generation for certain input types is hard to automate and therefore laborious. We propose a novel automated solution to test data generation that exploits existing web services as sources of realistic test data. Our approach is capable of generating realistic test data and also generating data based on tester-specified...
Multi-threaded applications are commonplace in today's software landscape. Pushing the boundaries of concurrency and parallelism, programmers are maximizing performance demanded by stakeholders. However, multi-threaded programs are challenging to test and debug. Prone to their own set of unique faults, such as race conditions, testers need to turn to automated validation tools for assistance. This...
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.