Qualcomm Incorporated

Ronald Karyodisa

Ying Hai Chen

Lei Wang

Ning Bi

Pengjun Huang

Techniques and systems are provided for prioritizing objects for object recognition in one or more video frames. For example, a current video frame is obtained, and a objects are detected in the current video frame. State information associated with the objects is determined. Priorities for the objects can also be determined. For example, a priority can be determined for an object based on state information associated with the object. Object recognition is performed for at least one object from the objects based on priorities determined for the at least one object. For instance, object recognition can be performed for objects having higher priorities before objects having lower priorities.

Prioritizing objects for object recognition

Techniques and systems are provided for performing object recognition for video frames. For example, one or more video frames of a first video are obtained. The one or more video frames have a first resolution and include one or more objects. The one or more objects are detected in the one or more video frames of the first video based on object detection being performed on the one or more video frames. One or more video frames of a second video are also obtained. The one or more video frames of the second video also include the one or more objects and have a second resolution that is greater than the first resolution. An object recognition process is performed on the one or more video frames of the second video to recognize or identify the one or more objects detected in the one or more video frames of the first video. In some cases, feedback associated with the object detection and/or the object recognition process can be obtained, and a resolution of the first video and/or a resolution of the second video can be adjusted based on the feedback.

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San Diego, CA, United States of America

Ronald Karyodisa