MMCVFeb 27, 2015

Hybrid coding of visual content and local image features

arXiv:1502.07828v18 citations
Originality Incremental advance
AI Analysis

This work addresses bandwidth limitations for distributed visual analysis applications like mobile visual search, offering an incremental improvement over existing paradigms.

The paper tackles the problem of inefficient bandwidth usage and coding artifacts in visual analysis applications by proposing a hybrid approach that jointly encodes visual content and local image features, achieving a target tradeoff between image quality and task accuracy through bitrate allocation.

Distributed visual analysis applications, such as mobile visual search or Visual Sensor Networks (VSNs) require the transmission of visual content on a bandwidth-limited network, from a peripheral node to a processing unit. Traditionally, a Compress-Then-Analyze approach has been pursued, in which sensing nodes acquire and encode the pixel-level representation of the visual content, that is subsequently transmitted to a sink node in order to be processed. This approach might not represent the most effective solution, since several analysis applications leverage a compact representation of the content, thus resulting in an inefficient usage of network resources. Furthermore, coding artifacts might significantly impact the accuracy of the visual task at hand. To tackle such limitations, an orthogonal approach named Analyze-Then-Compress has been proposed. According to such a paradigm, sensing nodes are responsible for the extraction of visual features, that are encoded and transmitted to a sink node for further processing. In spite of improved task efficiency, such paradigm implies the central processing node not being able to reconstruct a pixel-level representation of the visual content. In this paper we propose an effective compromise between the two paradigms, namely Hybrid-Analyze-Then-Compress (HATC) that aims at jointly encoding visual content and local image features. Furthermore, we show how a target tradeoff between image quality and task accuracy might be achieved by accurately allocating the bitrate to either visual content or local features.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes