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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...
A large number of studies have been reported on top-down influences of visual attention. However, less progress have been made in understanding and modeling its mechanisms in real-world tasks. In this paper, we propose an approach for learning spatial attention taking into account influences of physical actions on top-down attention. For this purpose, we focus on interactive visual environments (video...
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...
The most widely used cytogenetic method is G-banded karyotyping. A new feature extraction method is proposed for G-banded chromosome recognition. Chromosome features are mostly extracted on chromosome skeleton. The main innovation of the proposed method is extracting features around chromosome boundary contours, not the skeleton. The circular boundary contour signatures are extracted and applied to...
Centromere localization in human metaphase chromosomes is an essential task in many cytogenetic diagnosis procedures. The centromere location can be utilized to derive information such as the chromosome type, polarity assignment etc. Methods available in literature yield unreliable results mainly due to high variability of morphology in metaphase chromosomes and boundary noise in the image. In this...
Spatio-temporal interest points (STIPs) have recently become a mainstream technique for encoding human action video sequences. These local features overcome the complex issues of background subtraction and human tracking, and encode relevant motion information for recognition. Nonetheless, STIPs may result not only from actions themselves but from other factors such as person identity. This paper...
This study is a part of an ongoing project which aims to assist in teaching Sign Language (SL) to hearing-impaired children by means of non-verbal communication and imitation-based interaction games between a humanoid robot and a child. In this paper, the problem is geared towards a robot learning to imitate basic upper torso gestures (SL signs) using different machine learning techniques. RGBD sensor...
Automatic recognition of human actions from video has been studied for many years. Although still very difficult in uncontrolled scenarios, it has been successful in more restricted settings (e.g., fixed viewpoint, no occlusions) with recognition rates approaching 100%. However, the best-performing methods are complex and computationally-demanding and thus not well-suited for real-time deployments...
This paper presents advances on the Human ID Gait Challenge. Our method is based on combining an improved gait recognition method with an adapted low resolution face recognition method. For this, we experiment with a new automated segmentation technique based on alpha-matting. This allows better construction of feature images used for gait recognition. The same segmentation is also used as a basis...
For a natural communication robot cooperating with human, an adequate control mechanism of motion and utterance is required. This paper presents a robot motion planning method which considers utterance timing by utilizing Self-Organizing Map (SOM). Adequate target position of the robot motion and the utterance timing for an autonomous robot are decided by searching the best-matching-node on the SOM...
For the first time natural language processing approaches are applied on a large scale to psychometric methods. Psychometric methods have been applied in hundreds of thousands of published studies. This study examines automated approach to discovering behavioral knowledge that are encoded as constructs in social and behavioral science disciplines. To date, constructs relationships are ordinarily revealed...
Spoken Dialogue Systems (SDS) are natural language interfaces for human-computer interaction. User adaptive dialogue management strategies are essential to sustain the naturalness of interaction. In recent years data-driven methods for dialogue optimization have evolved to be a state of art approach. However these methods need vast amounts of corpora for dialogue optimization. In order to cope with...
Document summarization algorithms are most commonly evaluated according to the intrinsic quality of the summaries they produce. An alternate approach is to examine the extrinsic utility of a summary, measured by the ability of the summary to aid a human in the completion of a specific task. In this paper, we use topic identification as a proxy for relevancy determination in the context of an information...
Eating and drinking activity recognition can be considered a solitary research field in activity recognition area. The development of an application capable to identify human eating and drinking activity can be really useful in a smart home environment targeting to extend independent living of older persons in the early stages of dementia. In this paper a novel method aiming at eating and drinking...
When creating a ubiquitous service environment for humans, it is very important to be able to determine their location and movement. In this paper, we propose an algorithm that simultaneously estimates the number of humans and the movement locus for each human in a room, using only the binary sensing data obtained from infrared sensors attached to the ceiling. Compared to other camera-based systems,...
Since CMMB is an important application in wireless communication field -- its video quality plays a critical role for widely use. In assessment of video sequence, classic method often applies algebra method in making a compute model, such as PSNR, which often result in difficult for alignment of video sequence numbers and leads to complex computation problems. In this paper, it presents a novel method...
Face recognition is a biometric tool for authentication and verification having both research and practical relevance. A facial recognition based verification system can further be deemed a computer application for automatically identifying or verifying a person in a digital image. Varied and innovative face recognition systems have been developed thus far with widely accepted algorithms. The two...
This paper develops a general and formal frame-work for the ranking of web documents by considering the multimedia information contained in these documents. Multimedia information is mostly related to images and videos. Ranking can be treated as a combination of static and dynamic ranking. In this paper, we have described a static ranking method based on the analysis of the images present in the web...
The ever increasing availability of high speed Internet access has led to a leap in technologies that support real-time realistic interaction between humans in online virtual environments. In the context of this work, we wish to realise the vision of an online dance studio where a dance class is to be provided by an expert dance teacher and to be delivered to online students via the web. In this paper...
This paper proposes a soft voting based bag-of-features (BoF) model considering relative distance of the feature vectors to the nearest-neighbor codeword. Whereas state-of-the-art kernel distance based soft voting methods require brute force parameter optimization, which is time consuming, the proposed method does not require any optimization. The proposed algorithm was applied to human attribute...
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