In this paper, we present our approaches and results of high-level feature extraction and automatic video search in TRECVID-2007. In high-level feature extraction, our main focus is to explore the upper limit of bag-of-visualwords (BoW) approach based upon local appearance features. We study and evaluate several factors which could impact the performance of BoW. By considering these important f...

In this paper we study 3D convolutional networks for video understanding tasks. Our starting point is the stateof-the-art I3D model of [3], which “inflates” all the 2D filters of the Inception architecture to 3D. We first consider “deflating” the I3D model at various levels to understand the role of 3D convolutions. Interestingly, we found that 3D convolutions at the top layers of the network c...

We present our approach to TRECVID 2006, high-level feature extraction task. We submitted one run with type ‘A’, annotating all required 39 features. The approach was based on textual information extracted from speech recogniser and machine translation outputs. They were aligned with shots and associated with highlevel feature references. A list of significant words was created for each feature...

Traditionally, quadrature filters and derivatives have been considered as alternative approaches to low-level image analysis. In this paper we show that there actually exist close connections: We define the quadrature-based boundary tensor and the derivative-based gradient energy tensor which exhibit very similar behavior. We analyse the reason for this and determine how to minimize the differe...

Clothing fashion represents human’s aesthetic appreciation towards their outfits and reflects the development status of society, humanitarian and economics. Modelling fashion via machine is extremely difficult due to the fact that fashion is too abstract to be efficiently described by machine. In this paper, we delve into two fashion related problems: what type of image feature best describes f...

This work describes our contribution to the IEEE AASP Challenge on classification of acoustic scenes. From the 30 second long highly variable recordings, spectral, cepstral, energy and voicing-related audio features are extracted. A sliding window approach is used to obtain statistical functionals of the low-level features on short segments. SVM are used for classification of these short segmen...

When it comes to a computer vision system, automatic video event comprehension is a challenging task due to motion clutter, event understanding under complex scenes, multilevel semantic event inference, contextualization of events and views obtained from multiple cameras, unevenness of motion scales, shape changes, occlusions and object interactions among lots of other impairments. In recent ye...

Extracting features of components in an image is an important step for recognition of objects in the image. It is an intermediate-level image processing task as it transforms an image to a list of features. SIMD mesh-connected computers are considered natural architectures for low-level image processing tasks that transform an image into another image. In this paper, we design a fast general al...

This study proposes a mid-level feature descriptor and aims to validate improvement on image classification and retrieval tasks. In this paper, we propose a method to explore the conventional feature extraction techniques in the image classification pipeline from a different perspective where mid-level information is also incorporated in order to obtain a superior scene description. We hypothes...

the standards of endodontics have constantly been raised in the last 25 years by practitioners’ researches and their interest. most of the scientists believe the recent developments and the use of lasers as the most exciting achievement in endodontic treatment. nowadays, lasers are being used in endodontics to improve the prognosis of the root-filled teeth. the implement of suitable wavelengths...