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While bottom-up and top-down processes have shown effectiveness during predicting attention and eye fixation maps on images, in this paper, inspired by the perceptual organization mechanism before attention selection, we propose to utilize figure-ground maps for the purpose. So as to take both pixel-wise and region-wise interactions into consideration when predicting label probabilities for each pixel,...
In this paper we present the first large-scale scene attribute database. First, we perform crowd-sourced human studies to find a taxonomy of 102 discriminative attributes. Next, we build the “SUN attribute database” on top of the diverse SUN categorical database. Our attribute database spans more than 700 categories and 14,000 images and has potential for use in high-level scene understanding and...
In recent years, the rise of digital image and video data available has led to an increasing demand for image annotation. In this paper, we propose an interactive object annotation method that incrementally trains an object detector while the user provides annotations. In the design of the system, we have focused on minimizing human annotation time rather than pure algorithm learning performance....
The human vision tends to recognize more variants of a distinctive exemplar. This observation suggests that discriminative power of training exemplars could be utilized for shaping a desirable global classifier that generalizes maximally from a few exemplars. We propose to derive classification uncertainty for each exemplar, using a local classification task to separate the exemplar from those in...
Understanding natural human activity involves not only identifying the action being performed, but also locating the semantic elements of the scene and describing the person's interaction with them. We present a system that is able to recognize complex, fine-grained human actions involving the manipulation of objects in realistic action sequences. Our method takes advantage of recent advances in sensors...
This study was conducted to measure the readiness of PT Pertamina in implementing e-learning, where the study refers to the theories and methods of measurement have been developed by Aydin & Tasci. The results showed that PT Pertamina as a whole is ready for e-learning, but still need some improvement especially in the field of human resources. In addition, this study confirms that personal characteristics...
Reaching and grasping of objects in an everyday-life environment seems so simple for humans, though so complicated from an engineering point of view. Humans use a variety of strategies for reaching and grasping anything from the simplest to the most complicated objects, achieving high dexterity and efficiency. This seemingly simple process of reach-to-grasp relies on the complex coordination of the...
The studies on mirror neurons observed in monkeys indicate that recognition of other's actions activates neural circuits that are also responsible for generating the very same actions in the animal. The mirror neuron hypothesis argues that such an overlap between action generation and recognition can provide a shared worldview among individuals and be a key pillar for communication. Inspired by these...
In this paper, a novel sparse feature representation method for object tracking is proposed. The method is on the observation that a tracked object can be dynamically and compactly represented by a few features (sparse representation) from a large feature set (the improved histogram of oriented gradient and color, HOGC). Based on the HOGC features, the sparse representation can be learned online from...
Short Utterance Speaker Recognition (SUSR) is an important area of speaker recognition when only small amount of speech data is available for testing and training. We list the most commonly used state-of-the-art methods of speaker recognition and the significance of prosodic speaker recognition. A short survey of SUSR is hereby conducted, highlighting various methodologies when using short utterances...
Rehabilitation robotic devices have been actively explored for training patients with impaired neural functions or assisting those with weak limbs due to aging or diseases. In recent years, the authors have proposed light-weight exoskeleton designs for the upper arm, in which rigid links of the exoskeleton are replaced by lightweight cuffs attached to the moving limb segments of the human arm. Cables,...
This paper presents an adaptive neuro/fuzzy system which can be trained to detect the current human emotions from a set of measured responses. Six models are built using different types of input/output membership functions and trained by different kinds of input arrays. The models are compared based on their ability to train with lowest error values. Many factors impact the error values such as input/output...
Extracting and labeling sulcal curves on the human cerebral cortex is important for many neuroscience studies, however manually annotating the sulcal curves is a time-consuming task. In this paper, we present an automatic sulcal curve extraction method by registering a set of dense landmark points representing the sulcal curves to the subject cortical surface. A Markov random field is used to model...
This paper is an attempt to explore a human element not easily solved in the image processing communities. The problem statement is vague but important to address. What is a good image? More specifically, if a low contrast image is presented, at what level of enhancement is good enough for a human observer? This of course depends on diverse elements, e.g., personal preference, emotional state, physical...
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...
Current estimation methods for band level resolutions of human chromosome images in cytogenetic laboratories are time consuming and required experienced specialists to manually perform. To alleviate this problem, in this paper, a computerized approach to estimate band level resolution is proposed. The intensity gradient profile and sign profile of chromosome images are utilized to count the number...
The ability to recognize human activities from sensed information becomes more attractive to computer science researchers due to a demand on a high quality and low cost of health care services at anytime and anywhere. This work compares C-Support Vector Machine (C-SVM), Conditional Random Fields (CRF) and Linear Discriminant Analysis (LDA) for imbalanced dataset to perform automatic recognition of...
The objective of this research is to investigate the effect of design factors which consist of training content, training delivery, trainer competency and opportunity to use on small businesswomen's goal setting activities. The instrument for this research is adapted and modified from the Training Transfer Model and Model for Excellence (American Society of Training and Development Competency Research)...
The objective of the paper is to identify the factors and principles of soft skills and emotional intelligence which is lacked among the junior executive and is the primary cause of leadership failure in business organization today. This paper examines the gap, characteristics of soft skills and emotionally intelligence. It further highlighted the needs, systematic and step-by-step experiential approach...
Human activity recognition using wearable body sensors is playing a significant role in ubiquitous and mobile computing. One of the issues related to this wearable technology is that the captured activity signals are highly dependent on the location where the sensors are worn on the human body. Existing research work either extracts location information from certain activity signals or takes advantage...
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