DeepAI AI Chat
Log In Sign Up

Retrieval in Long Surveillance Videos using User Described Motion and Object Attributes

by   Greg Castanon, et al.

We present a content-based retrieval method for long surveillance videos both for wide-area (Airborne) as well as near-field imagery (CCTV). Our goal is to retrieve video segments, with a focus on detecting objects moving on routes, that match user-defined events of interest. The sheer size and remote locations where surveillance videos are acquired, necessitates highly compressed representations that are also meaningful for supporting user-defined queries. To address these challenges we archive long-surveillance video through lightweight processing based on low-level local spatio-temporal extraction of motion and object features. These are then hashed into an inverted index using locality-sensitive hashing (LSH). This local approach allows for query flexibility as well as leads to significant gains in compression. Our second task is to extract partial matches to the user-created query and assembles them into full matches using Dynamic Programming (DP). DP exploits causality to assemble the indexed low level features into a video segment which matches the query route. We examine CCTV and Airborne footage, whose low contrast makes motion extraction more difficult. We generate robust motion estimates for Airborne data using a tracklets generation algorithm while we use Horn and Schunck approach to generate motion estimates for CCTV. Our approach handles long routes, low contrasts and occlusion. We derive bounds on the rate of false positives and demonstrate the effectiveness of the approach for counting, motion pattern recognition and abandoned object applications.


page 1

page 3

page 4

page 7

page 8

page 9

page 11

page 12


Video Synopsis Generation Using Spatio-Temporal Groups

Millions of surveillance cameras operate at 24x7 generating huge amount ...

Spatio-Temporal Video Representation Learning for AI Based Video Playback Style Prediction

Ever-increasing smartphone-generated video content demands intelligent t...

Viewpoint distortion compensation in practical surveillance systems

Our aim is to estimate the perspective-effected geometric distortion of ...

Scene-driven Retrieval in Edited Videos using Aesthetic and Semantic Deep Features

This paper presents a novel retrieval pipeline for video collections, wh...

Circulant temporal encoding for video retrieval and temporal alignment

We address the problem of specific video event retrieval. Given a query ...

Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs

We present a novel framework for finding complex activities matching use...