In this paper, we propose a novel approach for traffic accident anticipation through (i) Adaptive Loss Early Anticipation (AdaLEA) and (ii) large-scale self-annotated incident database anticipation. The proposed AdaLEA allows model to gradually learn an earlier as training progresses. loss function adaptively assigns penalty weights depending on how early the can anticipate at each epoch. Additionally, construct Near-miss Incident DataBase This contains enormous number of near-miss videos...

Due to steady advancements in semiconductor technology, greatly-enhanced memory capacity and high-speed data processing are now available, creating many evolving types of audio video electronic products. The digital camera represents this trend well, where image sensor evolution has been responsible for enabling strong market growth. CCD sensors have contributed the miniaturization cameras by their continuous march toward smaller pixel size improved resolution, leading more megapixels...

The Hole-Accumulation Diode-Sensor (HAD-Sensor) structure, which allows to implement the variable speed electronic shutter in Interline Transfer (IT) CCD imaging sensor, has been developed. Based on this technology, a 2/3 inch sensor with 420,000 picture elements for consumer, industrial, and professional use was manufactured. theoretical lower limit of is about 1/1,000,000 sec. case exposure within vertical blanking interval (i.e. below 1/787 sec.). This HAD-Sensor achieves following five...

Change detection is the study of detecting changes between two different images a scene taken at times. The change methodology can provide us information in which area changed time by time. However, for application use, especially on disaster investigation, it highly required to understand not only where but also what are occurred high precision and resolution. paper proposes concept semantic detection, involves intuitively inserting meaning into detected areas. We mainly focus novel...

The paper presents a novel concept that analyzes and visualizes worldwide fashion styles. Our goal is to reveal web-based viral To achieve the fashion-based analysis, we have collected culture database (FCDB), which consists of 76 million geo-tagged images in 16 cosmopolitan cities. allows us grasp trend mixed styles with descriptor codeword vector. In order unveil trends FCDB, applied simple technique temporal subtraction between consecutive vectors two different times. experiments, show...

Simplified foreground Segmentation for a mobile video camera, such as camera on cell phone, is proposed. Unlike the static surveillance often used under various angles, including pan/tilt motions. The proposed algorithm, using transformed domain Gaussian Mixture model, can realize segmentation variety of angles without any pre-stored background model. parameters operation in small angle change are considered to be translation and amount found out by POC (Phase only correlation) operations...

Explainable AI (XAI) attempts to produce interpretable results from highly complex systems, but its form and effectiveness vary depending on the application domain. In this paper, we explore how XAI techniques can help graphic designers work advertising materials. A creative domain such as design is often characterized by a weak connection between individual business goal; e.g., small change in of banner result huge difference audience's reaction. We develop an system for that provides...

In online video understanding, which has a wide range of real-world applications, inference speed is crucial. Many approaches involve frame-level visual feature extraction, often represents the biggest bottleneck. We propose RetinaViT, an efficient method for extracting features in stream, aiming to fundamentally enhance efficiency understanding tasks. RetinaViT composed efficiently approximated Transformer blocks that only take changed tokens (event tokens) as queries and reuse already...

This paper presents an approach to decomposing animated graphics into sprites, a set of basic elements or layers. Our builds on the optimization sprite parameters fit raster video. For efficiency, we assume static textures for sprites reduce search space while preventing artifacts using texture prior model. To further speed up optimization, introduce initialization utilizing pre-trained video object segmentation model and user input single frame annotations. our study, construct Crello...

Clustering is a technique of unsupervised classification. The methods are classified into two types, one hierarchical and the other non-hierarchical. Fuzzy non-metric model (FNM) representative method non-hierarchical clustering. FNM very useful because belongingness or membership degree each datum to cluster calculated directly from dissimilarities between data, centers not used. However cannot handle data with uncertainty, called uncertain e.g. incomplete which have errors. In order such...

The fuzzy non-metric model (FNM) is a representative non-hierarchical clustering method, which very useful because the belongingness or membership degree of each datum to cluster can be calculated directly from dissimilarities between data and centers are not used. However, original FNM cannot handle with uncertainty. In this study, we refer uncertainty as “uncertain data,” e.g., incomplete that have errors. Previously, methods was proposed based on concept tolerance vector for handling...

Video ads segmentation and tagging is a challenging task due to two main reasons: (1) the video scene structure complex (2) it includes multiple modalities (e.g., visual, audio, text.). While previous work focuses mostly on activity videos (e.g. "cooking", "sports"), not clear how they can be leveraged tackle of content structuring. In this paper, we propose two-stage method that first provides boundaries scenes, then combines confidence score for each segmented tag classes predicted scene....

The authors have developed a system to autonomously classify the meanings of words using knowledge database constructed from sentences found in textual content on Internet websites. This is totally new for classifying dynamically only connections between words. believe that robots such can approximate humans.

In this paper, we propose a method of human action recognition for videos in which actions are continuously transitioning. First, make pose estimator has learned joint coordinates using Convolutional Neural Networks (CNN) and extract feature from intermediate structure it. Second, train recognizer structured by Long Short-Term Memory (LSTM), environmental as inputs. At that time, Pose-Centric Learning. addition, calculate Attention represents importance each element, filtering latter to...

In this paper, we propose a novel approach for traffic accident anticipation through (i) Adaptive Loss Early Anticipation (AdaLEA) and (ii) large-scale self-annotated incident database anticipation. The proposed AdaLEA allows model to gradually learn an earlier as training progresses. loss function adaptively assigns penalty weights depending on how early the can an- ticipate at each epoch. Additionally, construct Near-miss Incident DataBase This contains enormous number of near- miss videos...

Abstract not Available.