We propose a motion segmentation algorithm for extracting foreground objects with a pan-tilt camera. Segmentation is achieved by spatio-temporal filtering of the scene to model the background. Temporal filtering is done by a set of modified AR (Auto-Regressive) filters which model the background statistics for a particular view of the scene. Backgrounds from different views of the pan-tilt came...

Video surveillance has been used in many monitoring security sensitive areas such as banks, department stores, highways, crowded public places and borders. Detecting moving regions such as vehicles and people is the first basic step of almost every vision system, because it provides a focus of attention and simplifies the processing on subsequent analysis steps. It is one of the most difficult ...

The necessity of temporal stability in partition sequences for segmentation-based video coding techniques is stated. A time recursive segmentation approach is analyzed under this scope. The structure of this approach has ve main steps: Partition projection, Image modeling, Image simpliication, Marker extraction and Decision. New techniques are proposed to improve the Partition projection in ord...

We describe a simple new technique for spatio-temporal segmentation of video sequences. Each pixel of a 3D space-time video stack is mapped to a 7D feature point whose coordinates include three color components, two motion angle components and two motion position components. The clustering of these feature points provides color segmentation and motion segmentation, as well as a consistent label...

Many future video standards such as MPEG-4 are shifting focus from compression to content; Video Object Segmentation is the key technology required by these standards. Unlike still images, motion in video can be used to discriminate between objects. We present an automatic video single object segmentation system whose core is the adaptive version of the Circular Viterbi algorithm. The Circular ...

In this paper, we present a novel learning-based algorithm for temporal segmentation of a video into clips based on both camera and scene motion, in particular, based on combinations of static vs. dynamic camera and static vs. dynamic scene. Given a video, we first perform shot boundary detection to segment the video to shots. We enforce temporal continuity by constructing a Markov Random Field...

In the previous part of this paper, we presented an active object segmentation system which can be used to extract semantic video objects with accurate boundaries. New video representations based on these semantic objects provide great potential for content-based video searching. In this part, we present a new content-based video object searching system. The system uses a novel query model whic...

We propose a new principle for recognizing fingerspelling sequences from American Sign Language (ASL). Instead of training a system to recognize the static posture for each letter from an isolated frame, we recognize the dynamic gestures corresponding to transitions between letters. This eliminates the need for an explicit temporal segmentation step, which we show is error-prone at speeds used ...

A video shot is defined as a continuously imaged temporal segment of a video. Since the semantic content of a video is largely based on its production (imaging) process, the complete segmentation of a video into shots is a fundamental first step for most kinds of semantic video processing tasks. Here we present a classification of shot boundary detection algorithms, including those that deal wi...

Motion-based segmentation is traditionally used for video object extraction. Objects are detected as groups of significant moving regions and tracked through the sequence. However, this approach presents difficulties for video shots that contain both static and dynamic moments, and detection is prone to fail in absence of motion. In addition, retrieval of static contents is needed for high-leve...