The advent of mobile devices and media cloud services has led to the unprecedented growth of personal photo collections. One of the fundamental problems in managing the increasing number of photos is automatic image tagging. Image tagging is the task of assigning human-friendly tags to an image so that the semantic tags can better reflect the content of the image and therefore can help users be...

1 Pedestrians and cyclists are vulnerable road users and despite their limited presence in traffic events, these 2 two groups have the most collisions resulting in injuries and fatalities. Due to problems regarding data 3 collection for pedestrians and cyclists, there is a shortcoming in the field of road safety with regards to the 4 availability and quality of data for non-motorized modes. Als...

Crowdsourcing annotation is a recent development since a complete and elaborate annotation of the content of an image is an extremely labour-intensive and time consuming task. In this paper we examine the possibility to build accurate visual models for keywords created through crowdsourcing. Specifically, 8 different keywords related to athletics domain have been modelled using MPEG-7 and Histo...

Pattern clustering is an important data analysis process useful in a wide spectrum of computer vision applications. In addition to choosing the appropriate clustering methods, particular attention should be paid to the choice of the features describing patterns in order to improve the clustering performance. This paper presents a novel feature descriptor, referred as Histogram of Structure Tens...

With the development of low cost aerial optical sensors having a spatial resolution in the range of few centimetres, the traffic monitoring by plane receives a new boost. The gained traffic data are very useful in various fields. Near real-time applications in the case of traffic management of mass events or catastrophes and non time critical applications in the wide field of general transport ...

We introduce a parallel implementation of the histogram of oriented gradients algorithm for object detection. Our implementation uses the GPU and the NVIDIA CUDA framework. We achieve speedups of over 67x from the standard sequential code, using a single video card. Furthermore it supports multiple video cards so speedups of 120x or more can be achieved. This allows us to achieve real-time perf...

A hardware implementation of a computationally light, scale, and rotation invariant method for shape detection on FPGA is devised. The method is based on histogram of oriented gradients (HOG) and average magnitude difference function (AMDF). AMDF is used as a decision module that measures the similarity/dissimilarity between HOG vectors of an image in order to classify the object. In addition, ...

In this paper, an effective method is proposed to handle the facial expression recognition problem. The system detects the face and facial components including eyes, brows and mouths. Since facial expressions result from facial muscle movements or deformations, and Histogram of Oriented Gradients (HOG) is very sensitive to the object deformations, we apply the HOG to encode these facial compone...

We implement lane detection using edge detection, Hough transforms, and vanishing point filtering in Hough space; the car detection is implemented by using histogram of oriented gradients feature descriptors and classified by linear support vector machines. Hard-negative mining is applied to alleviate detection of false positives; with the information of vanishing point along with prior knowled...

Content based image retrieval is the technique to retrieve similar images from a database that are visually similar to a given query image. It is an active and emerging research field in computer vision. In our proposed system, the Interest points based Histogram of Oriented Gradients (HOG) feature descriptor is used to retrieve the relevant images from the database. The dimensionality of the H...