Streaming systems are an increasingly appealing substrate for managing video data via the stream abstraction. However, if we consider a large stream collection, it can be hard for data scientists to discover and locate relevant videos, let alone specific ...

The rapid evolution of multimedia and computer vision technologies requires adaptive visual model deployment strategies to effectively handle diverse tasks and varying environments. This work introduces AxiomVision, a novel framework that can guarantee ...

Retrieval-augmented generation (RAG) systems combine the strengths of language generation and information retrieval to power many real-world applications like chatbots. Use of RAG for understanding of videos is appealing but there are two critical ...

Localizing video moments based on the movement patterns of objects is an important task in video analytics. Existing video analytics systems offer two types of querying interfaces based on natural language and SQL, respectively. However, both types of ...

With the advancement of modern artificial intelligence techniques, computer vision can play a vital role in enhancing roadway safety by reducing the risk of imminent collisions. To do so, a vision-based safety application is required, where a roadside ...

AI/ML techniques have been used to solve systems problems, but their applicability to customize solutions on-the-fly has been limited. Traditionally, any customization required manually changing the AI/ML model or modifying the code, configuration ...

While existing strategies to execute deep learning-based classification on low-power platforms assume the models are trained on all classes of interest, this paper posits that adopting context-awareness i.e. narrowing down a classification task to the ...

Obstructive sleep apnea (OSA) is a prevalent sleep disorder, affecting approximately one billion individuals globally. In this study, we aim to address the limitations of Polysomnography (PSG), the gold standard for OSA diagnosis, by developing SlAction, ...

Scalable video query optimization has re-emerged as an attractive research topic in recent years. The OTIF system, a video database with cutting-edge efficiency, has introduced a new paradigm of utilizing view materialization to facilitate online query ...

The human visual system's strongest suit is its ability to detect and follow moving objects. The rise of video-based applications like surveillance, traffic monitoring, military security, robot navigation, etc. may be attributed to the widespread ...

CCTV (Closed-Circuit Television) systems are commonly used for security and surveillance. They provide a visual record of events, which can be used to monitor criminal activity, support investigations, and improve public safety. Many cities have ...

Computer-vision algorithms have been used to enhance hands-free user interactions with smart systems. Traditional approaches for object and gesture detection and recognition are through the processing of video frames by convolutional neural networks (...

Offloading computing to edge servers is a promising solution to support growing video understanding applications at resource-constrained IoT devices. Recent efforts have been made to enhance the scalability of such systems by reducing inference costs on ...

While large deep neural networks excel at general video analytics tasks, the significant demand on computing capacity makes them infeasible for real-time inference on resource-constrained end cameras. In this paper, we propose an edge-assisted framework ...

The delay to obtain analysis results is an important metric in video analytics. Previous work has focused on reducing frame transmission and inference delay to optimize total delay. However, network fluctuations can cause frames to arrive at the backend ...

Deep learning–based video analytics demands high network bandwidth to ferry the large volume of data when deployed on the cloud. When incorporated at the edge side, only lightweight deep neural network (DNN) models are affordable due to computational ...

Intelligent video analytics is resource-intensive, e.g. computation and bandwidth. In this paper, we improve resource efficiency for intelligent video analytics via proposing a distributed architecture named EVA. We noticed that timeliness of anomaly ...

Recently the edge-assisted method has been proposed as a promising technique to deliver fast video analytics by partitioning frames into multiple blocks for parallel execution in edge servers. However, the problem of dispatching tasks over edge servers ...

The wide use of cameras in the past decade has increased the need to process video data significantly. Due to the large volume of video data, analyzing videos to extract useful information has become a critical challenge. Several prior works have ...

We assess different motives underlying mask-wearing behaviors and discuss novel strategies for segmenting customers based on the motives.

In 2020, as the novel coronavirus spread globally, face masks were recommended in public settings to protect against and slow down viral transmission. People complied to varying extents, and their reactions may have been driven by a variety of ...