In this paper, we propose a method to analyze gender of the pedestrian and whether he or she has a baggage or not in a public space. The challenging part of this work is we only use top-view camera images to protect the pedestrians’ privacy. We focused on temporal changes in their position, shape, and contours over the frames because their appearances do not provide much information. We extract...

Pedestrian detection is a critical issue in computer vision, with several feature descriptors can be adopted. Since the ability of various kinds of feature descriptor is different in pedestrian detection and there is no basis in feature selection, we analyze the commonly used features in theory and compare them in experiments. It is desired to find a new feature with the strongest description a...

This paper shows how to reduce the computational cost for a variety of common machine vision tasks by operating directly in the compressed domain, particularly in the context of hardware acceleration. Pyramid Vector Quantization (PVQ) is the compression technique of choice and its properties are exploited to simplify Support Vector Machines (SVM), Convolutional Neural Networks(CNNs), Histogram ...

Osteoarthritis (OA) is a common musculoskeletal condition typically diagnosed from radiographic assessment after clinical examination. However, a visual evaluation made by a practitioner suffers from subjectivity and is highly dependent on the experience. Computeraided diagnostics (CAD) could improve the objectivity of knee radiographic examination. The first essential step of knee OA CAD is to...

In this paper, we present a new algorithm to detect the two-wheelers riding on people for the normalized cross correlation (NCC) and its application of histogram of oriented gradients (HOGs). Using the NCC algorithm, local geometric information is used as weighting value to the HOG features. Experimental results show that the new approach gives higher detection accuracy than that of the convent...

Automatically detecting facial expressions has become an important research area. It plays a significant role in security, human-computer interaction and health-care. Yet, earlier work focuses on posed facial expression. In this paper, we propose a spontaneous facial expression recognition method based on effective feature extraction and facial expression recognition for Micro Expression analys...

Most previous work of facial action recognition focused only on verifying whether a certain facial action unit appeared or not on a face image. In this paper, we report our investigation on the semantic relationships of facial action units and introduce a novel method for facial action unit recognition based on action unit classifiers and a Bayes network called Facial Action Unit Association Ne...

The histogram of oriented gradients (HOG)[3] is a widely used feature descriptor in computer vision for the purpose of object detection. In the paper, a modified HOG descriptor is described, it uses a lookup table and the method of integral image[2][4] to speed up the detection performance by a factor of 5∼10. By exploiting the special hardware features of a given platform(e.g. a digital signal...

Pedestrian tracking and detection of crowd abnormal activity under dynamic and complex background using Intelligent Video Surveillance (IVS) system are beneficial for security in public places. This paper presents a pedestrian tracking method combing Histogram of Oriented Gradients (HOG) detection and particle filter. This method regards the particle filter as the tracking framework, identifies...

We present a fully automated system for segmenting the Left Ventricle (LV) in cardiac MR images based on statistical and deformable models. A Project-Out Inverse Compositional Active Appearance Model of 3D LV shape produces segmentations that are refined using a unified statistical/deterministic deformable model. A new multi-scale detector, based on the Histogram of Oriented Gradients (HoG), pr...