Clustering-based object classification

A surveillance system configured to identify objects in video content captured by a video camera, the system comprising:

• means for receiving video content of a scene captured by a video camera;
• means for detecting an object in the video content;
• means for identifying a track that the object follows over a series of frames of the video content;
• means for extracting object features for the object from the video content;
• and
• means for classifying the object based on the object features, wherein classifying the object further comprises:
• means for determining a track-level classification for the object using spatially invariant object features;
• means for determining a global-clustering classification for the object using spatially variant features;
• and
• means for determining an object type for the object based on the track-level classification and the global-clustering classification for the object.

A surveillance system for identifying objects in video content captured by a video camera, the system comprising:

• a tangible, non-transitory computer-readable memory;
• a plurality of modules comprising processor executable code stored in the memory;
• a processor connected to the memory and configured to access the plurality of modules stored in the memory;
• and
• a video processing module configured to:
• receive video content of a scene captured by a video camera;
• detect an object in the video content;
• identify a track that the object follows over a series of frames of the video content;
• extract object features for the object from the video content;
• and
• classify the object based on the object features, wherein to classify the object the video processing module is further configured to:
• determine a track-level classification for the object using spatially invariant object features;
• determine a global-clustering classification for the object using spatially variant features;
• and
• determine an object type for the object based on the track-level classification and the global-clustering classification for the object.

A tangible computer-readable medium, having stored thereon computer-readable instructions identifying objects in video content, comprising instructions configured to cause a computer to:

• receive video content of a scene captured by a video camera;
• detect an object in the video content;
• identify a track that the object follows over a series of frames of the video content;
• extract object features for the object from the video content;
• and
• classify the object based on the object features, wherein the instruction to cause the computer to classify the object further comprise instructions to cause the computer to:
• determine a track-level classification for the object using spatially invariant object features;
• determine a global-clustering classification for the object using spatially variant features;
• and
• determine an object type for the object based on the track-level classification and the global-clustering classification for the object.